infrared thermography reading 2

Infrared Thermal TestingReading IIMy ASNT Level III Pre-Exam Preparatory Self Study Notes 26th April 2015

Charlie Chong/ Fion Zhang

Infrared Thermography


Fion Zhang at Shanghai27th May 2015

http://meilishouxihu.blog.163.com/


Charlie Chong/ Fion Zhang http://greekhouseoffonts.com/


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IVONA TTS Capable.

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Reading 1The Ultimate Infrared Handbook for R&D ProfessionalsContents1. IR Thermography – How It Works 2. IR Detectors For Thermographic Imaging3. Getting The Most From Your IR Camera4. Filters Extend IR Camera Usefulness 5. Ultra High-Speed Thermography

http://www.flirmedia.com/MMC/THG/Brochures/T559243/T559243_EN.pdf


Chapter 1: IR Thermography - How It WorksIR Thermography CamerasAlthough infrared radiation (IR) is not detectable by the human eye, an IR camera can convert it to a visual image that depicts thermal variations across an object or scene. IR covers a portion of the electromagnetic spectrum from approximately 900 to 14,000 nanometers (0.9 μm–14 μm). IR is emitted by all objects at temperatures above absolute zero, and the amount of radiation increases with temperature. Thermography is a type of imaging that is accomplished with an IR camera calibrated to displaytemperature values across an object or scene. Therefore, thermography allows one to make non-contact measurements of an object’s temperature. IR camera construction is similar to a digital video camera, see Figure 1.1.

Figure 1.1. Simplified block diagram of an IR camera



The main components are a lens that focuses IR onto a detector, pluselectronics and software for processing and displaying the signals and images. Instead of a charge coupled device that video and digital still cameras use, the IR camera detector is a focal plane array (FPA) of micrometer size pixels made of various materials sensitive to IR wavelengths. FPA resolution can range from about 160 × 120 pixels up to 1024 × 1024 pixels. Certain IR cameras have built-in software that allows the user to focus on specific areas of the FPA and calculate the temperature. Other systems utilized a computer or data system with specialized software that providestemperature analysis. Both methods can supply temperature analysis with better than ±1°C precision. FPA detector technologies are broken down into two categories: thermal detectors and quantum detectors. A common type of thermal detector is an uncooled microbolometer made of a metal or semiconductor material. These typically have lower cost and a broader IR spectral response than quantum detectors.

Keywords:FPA detector technologies are broken down into two categories: thermaldetectors and quantum detectors.



Still, microbolometers react to incident radiant energy and are much lowerand less sensitive than quantum detectors. Quantum detectors are madefrom materials such as InSb, InGaAs, PtSi, HgCdTe (MCT), and layeredGaAs/AlGaAs for QWIP (Quantum Well Infrared Photon) detectors. Theoperation of a quantum detector is based on the change of state of electronsin a crystal structure reacting to incident photons. These detectors aregenerally faster and more sensitive than thermal detectors. However, theyrequire cooling, sometimes down to cryogenic temperatures using liquid nitrogen or a small Stirling cycle refrigerator unit.

Ga GalliumIn IndiumSi SiliconAs ArsenicSb AntimonyHg MercuryCd CadmiumTe TelluriumAl Aluminum



IR Spectrum ConsiderationsTypically, IR cameras are designed and calibrated for a specific range of theIR spectrum. This means that the optics and detector materials must beselected for the desired range. Figure 1.2 illustrates the spectral responseregions for various detector materials. Because IR has the same propertiesas visible light regarding reflection, refraction, and transmission, the optics forthermal cameras are designed in a fashion similar to those of a visualwavelength camera. However, the types of glass used in optics for visiblelight cameras cannot be used for optics in an infrared camera, as they do nottransmit IR wavelengths well enough. Conversely, materials that aretransparent to IR are often opaque to visible light. IR camera lenses typicallyuse silicon (Si) and germanium (Ge) materials. Normally Si is used for MWIR(medium wavelength IR) camera systems, whereas Ge is used in LW (longwavelength) cameras. Si and Ge have good mechanical properties, i.e., theydo not break easily, they are nonhygroscopic, and they can be formed intolenses with modern turning methods. As in visible light cameras, IR cameralenses have antireflective coatings. With proper design, IR camera lenses cantransmit close to 100% of incident radiation.



Figure 1.2. Examples of detector materials and their spectral responses relative to IR mid wave (MW) and long wave (LW) bands

InSb, InGaAs, PtSi, HgCdTe (MCT), and layered GaAs/AlGaAs for QWIP (Quantum Well Infrared Photon) detectors.



Thermal Radiation PrinciplesThe intensity of the emitted energy from an object varies with temperature andradiation wavelength. If the object is colder than about 500°C, emitted radiation lies completely within IR wavelengths. In addition to emitting radiation, an object reacts to incident radiation from its surroundings by absorbing and reflecting a portion of it, or allowing some of it to pass through (as through a lens). From this physical principle, the Total Radiation Law is derived, which can be stated with the following formula:

W = αW + ρW +τW,

which can be simplified to: 1 = α+ ρ +τ ,

The coefficients a, r, and t describe the object’s incident energy absorbtion alpha (α),reflection Rho (ρ), and transmission Tau (τ ). Each coefficient can have a value fromzero to one, depending on how well an object absorbs, reflects, or transmits incidentradiation. For example, if ρ = 0, τ = 0, and α = 1, then there is no reflected or transmitted radiation, and 100% of incident radiation is absorbed. This is called a perfect blackbody. In the real world there are no objects that are perfect absorbers, reflectors, or transmitters, although some may come very close to one of these properties. Nonetheless, the concept of a perfect blackbody is very important in thescience of thermography, because it is the foundation for relating IR radiation to an object’s temperature.



Keywords: Object’s incident energy: absorbtion alpha (α), reflection Rho (ρ), transmission Tau (τ ), emissivity epsilon (Ɛ).



Fundamentally, a perfect blackbody is a perfect absorber and emitter ofradiant energy. This concept is stated mathematical as Kirchhoff’s Law. Theradiative properties of a body are denoted by the symbol Ɛ, the emittance oremissivity of the body. Kirchhoff’s law states that α = Ɛ, and since both valuesvary with the radiation wavelength, the formula can take the form α(λ) = Ɛ(λ),where λ denotes the wavelength.

The total radiation law can thus take the mathematical form 1 = Ɛ + ρ + τ, which for an opaque body (τ = 0) can be simplified to 1 = Ɛ + ρ or ρ = 1 – Ɛ(i.e., reflection = 1 – emissivity). Since a perfect blackbody is a perfect absorber, ρ = 0 and Ɛ = 1. The radiative properties of a perfect blackbody can also be described mathematically by Planck’s Law. Since this has a complex mathematical formula, and is a function of temperature and radiationwavelength, a blackbody’s radiative properties are usually shown as a seriesof curves (Figure 1.3).



Figure 1.3. Illustration of Planck’s Law


W α T4


Wien’s displacement lawThese curves show the radiation per wavelength unit and area unit, called the spectral radiant emittance of the blackbody. The higher the temperature, the more intense the emitted radiation. However, each emittance curve has adistinct maximum value at a certain wavelength. This maximum can becalculated from Wien’s displacement law,

λmax = 2898/T, or (λmax x T = 2.898 x 10-3 m.K)

where T is the absolute temperature of the blackbody, measured in Kelvin (K), and λmax is the wavelength at the maximum intensity (in μm). Using blackbody emittance curves, one can find that an object at 30°C has a maximum near 10μm, whereas an object at 1000°C has a radiant intensity with a maximum of near 2.3μm. The latter has a maximum spectral radiant emittance about 1,400 times higher than a blackbody at 30°C, with a considerable portion of the radiation in the visible spectrum.

http://www.flirmedia.com/MMC/THG/Brochures/T559243/T559243_EN.pdfc


Wien’s displacement lawThese curves show the radiation per wavelength unit and area unit, called the spectral radiant emittance of the blackbody. The higher the temperature, the more intense the emitted radiation. However, each emittance curve has adistinct maximum value at a certain wavelength. This maximum can becalculated from Wien’s displacement law,

λmax = 2898/T, or (λmax x T = 2.898 x 10-3 m.K)

where T is the absolute temperature of the blackbody, measured in Kelvin (K), and λmax is the wavelength at the maximum intensity (in μm). Using blackbody emittance curves, one can find that an object at 30°C has a maximum near 10μm, whereas an object at 1000°C has a radiant intensity with a maximum of near 2.3μm. The latter has a maximum spectral radiant emittance about 1,400 times higher than a blackbody at 30°C, with a considerable portion of the radiation in the visible spectrum.

λmax in meter, T in Kelvin.

http://hyperphysics.phy-astr.gsu.edu/hbase/wien.html


Wien's Displacement Law When the temperature of a blackbody radiator increases, the overall radiated energy increases and the peak of the radiation curve moves to shorter wavelengths. When the maximum is evaluated from the Planck radiation formula, the product of the peak wavelength and the temperature is found to be a constant.

http://hyperphysics.phy-astr.gsu.edu/hbase/wien.html#c3


This relationship is called Wien's displacement law and is useful for the determining the temperatures of hot radiant objects such as stars, and indeed for a determination of the temperature of any radiant object whose temperature is far above that of its surroundings.

It should be noted that the peak of the radiation curve in the Wien relationship is the peak only because the intensity is plotted as a function of wavelength. If frequency or some other variable is used on the horizontal axis, the peak will be at a different wavelength.



Wien's displacement law states that the black body radiation curve for different temperatures peaks at a wavelength inversely proportional to the temperature. The shift of that peak is a direct consequence of the Planck radiation law which describes the spectral brightness of black body radiation as a function of wavelength at any given temperature. However it had been discovered by Wilhelm Wien several years before Max Planck developed that more general equation, and describes the entire shift of the spectrum of black body radiation toward shorter wavelengths as temperature increases. Formally, Wien's displacement law states that the spectral radiance of black body radiation per unit wavelength, peaks at the wavelength λmaxgiven by:

λmax x T = b (2.898 x 10-3 m.K)

where T is the absolute temperature in Kelvin. b is a constant of proportionality called Wien's displacement constant, equal to 2.8977721(26)×10−3 m K. If one is considering the peak of black body emission per unit frequency or per proportional bandwidth, one must use a different proportionality constant. However the form of the law remains the same: the peak wavelength is inversely proportional to temperature (or the peak frequency is directly proportional to temperature). Wien's displacement law may be referred to as "Wien's law", a term which is also used for the Wien approximation.

http://en.wikipedia.org/wiki/Wien%27s_displacement_law


Stefan-Bolzmann lawFrom Planck’s law, the total radiated energy W from a blackbody can becalculated. This is expressed by a formula known as the Stefan-Bolzmannlaw:

W = σ ∙ T4 (W/m2), (here the emissivity Ɛ was assumed =1)

where σ is the Stefan-Bolzmann’s constant (5.67 × 10–8 W/m2K4). As anexample, a human being with a normal temperature (about 300 K) will radiateabout 500W/ m2 of effective body surface. As a rule of thumb, the effectivebody surface is 1m2, and radiates about 0.5kW - a substantial heat loss. Theequations described in this section provide important relationships betweenemitted radiation and temperature of a perfect blackbody. Since most objectsof interest to thermographers are not perfect blackbodies, there needs to besome way for an IR camera to graph the temperature of a “normal” object.



Wien's displacement law & Stefan-Bolzmann law: Blackbody Radiation, Modern Physics, Quantum Mechanics, and the Oxford Comma | Doc Physics

■ https://www.youtube.com/embed/GgD3Um_f0DQ

https://www.youtube.com/watch?v=GgD3Um_f0DQ


Wien's displacement law & Stefan-Bolzmann law: Max Planck Solves the Ultraviolet Catastrophe for Blackbody Radiation | Doc Physics

■ https://www.youtube.com/embed/H-7f-3OAXm0

https://www.youtube.com/watch?v=H-7f-3OAXm0


Radiation Curves (Intensity Plot)

The wavelength of the peak of the blackbody radiation curve decreases in a linear fashion ? as the temperature is increased (Wien's displacement law). This linear variation is not evident in this kind of plot since the intensity increases with the fourth power of the temperature (Stefan- Boltzmann law). The nature of the peak wavelength change is made more evident by plotting the fourth root of the intensity.



Radiation Curves (Intensity Plot)



SummarizingHow a perfect black body changes with temperatures?

The λmax changes in a linear manner ? ( inversely proportionally)according to Wien's Displacement Law

The total total radiated energy W changes in a fourth power T4

proportionally according to Stefan-Bolzmann law



Wien's displacement law (inverse proportional relation)λmax x T = b λmax = b∙1/T



Emissivity ƐThe radiative properties of objects are usually described in relation to a perfect blackbody (the perfect emitter). If the emitted energy from a blackbody is denoted as Wbb, and that of a normal object at the same temperature as Wobj, then the ratio between these two values describes the emissivity (Ɛ) of the object, Ɛ = Wobj / Wbb. Thus, emissivity is a number between 0 and 1.

The better the radiative properties of the object, the higher its emissivity. An object that has the same emissivity Ɛ for all wavelengths is called a greybody.Consequently, for a greybody, Stefan- Bolzmann’s law takes the form:

W = Ɛ∙σ∙T4 (W/m2),

which states that the total emissive power of a greybody is the same as thatof a blackbody of the same temperature reduced in proportion to the value of Ɛ for the object.

Keywords:Greybody



■ωσμ∙Ωπ∆º≠δ≤>ηθφФρ|β≠Ɛ∠ ʋ λ α ρτ

http://www.webexhibits.org/causesofcolor/3.html


Still, most bodies are neither blackbodies nor greybodies. The emissivityvaries with wavelength. As thermography operates only inside limited spectralranges, in practice it is often possible to treat objects as greybodies. In anycase, an object having emittance that varies strongly with wavelength iscalled a selective radiator. For example, glass is a very selective radiator,behaving almost like a blackbody for certain wavelengths, whereas it is ratherthe opposite for other wavelengths. Atmospheric Influence Between theobject and the thermal camera is the atmosphere, which tends to attenuate radiation due to absorption by gases and scattering by particles. The amount of attenuation depends heavily on radiation wavelength. Although the atmosphere usually transmits visible light very well, fog, clouds, rain, and snow can prevent us from seeing distant objects. The same principle applies to infrared radiation.

Keywords:BlackbodyGreybodyselective radiator



For thermographic measurement we must use the so-called atmospheric windows. As can be seen from Figure 1.4, they can be found between 2 -5μm, the mid-wave windows, and 7.5μm – 13.5μm, the long-wave window.

Atmospheric attenuation prevents an object’s total radiation from reaching the camera. If no correction for attenuation is applied, the measured apparent temperature will be lower and lower with increased distance. IR camera software corrects for atmospheric attenuation. Typically, LW cameras in the 7.5μm to13.5μm range work well anywhere that atmospheric attenuation is involved, because the atmosphere tends to act as a high-pass filter above 7.5μm (Figure 4). The MW band of 3–5μm tends to be employed with highly sensitive detectors for high end R&D and military applications. When acquiring a signal through the atmosphere with MW cameras, selected transmission bands must be used where less attenuation takes place.

From other reading: Short-wave systems in particular are susceptible to attenuation by the atmosphere and, as a result, correction for relative humidity and distance to object are recommended.



Figure 1.4. Atmospheric attenuation (white areas) with a chart of the gases and water vapor causing most of it. The areas under the curve represent the highest IR transmission.



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Charlie Chong/ Fion Zhang http://www.flirmedia.com/MMC/THG/Brochures/T559243/T559243_EN.pdf


Figure 4. Atmospheric attenuation (white areas) with a chart of the gases and water vapor causing most of it. The areas under the curve represent the highest IR transmission.

http://www.universe-galaxies-stars.com/infrared.html


Figure 4. Atmospheric attenuation (white areas) with a chart of the gases and water vapor causing most of it. The areas under the curve represent the highest IR transmission.



Raleigh ScatteringRayleigh scattering, named after the British physicist Lord Rayleigh is the (dominantly) elastic scattering of light or other electromagnetic radiation by particles much smaller than the wavelength of the radiation. The Rayleigh scattering does not change the state of material hence it is a parametric process. The particles may be individual atoms or molecules. It can occur when light travels through transparent solids and liquids, but is most prominently seen in gases. Rayleigh scattering results from the electric polarizability of the particles. The oscillating electric field of a light wave acts on the charges within a particle, causing them to move at the same frequency. The particle therefore becomes a small radiating dipole whose radiation we see as scattered light.

Rayleigh scattering of sunlight in the atmosphere causes diffuse sky radiation, which is the reason for the blue color of the sky and the yellow tone of the sun itself.

For historical reasons, Rayleigh scattering of molecular nitrogen and oxygen in the atmosphere includes elastic scattering as well as the inelastic contribution from rotational Raman scattering in air, since the changes in wave number of the scattered photon are typically smaller than 50 cm−1. This can lead to changes in the rotational state of the molecules. Furthermore the inelastic contribution has the same wavelengths dependency as the elastic part.

Scattering by particles similar to, or larger than, the wavelength of light is typically treated by the Mie theory, the discrete dipole approximation and other computational techniques. Rayleigh scattering applies to particles that are small with respect to wavelengths of light, and that are optically "soft" (i.e. with a refractive index close to 1). On the other hand, Anomalous Diffraction Theory applies to optically soft but larger particles.

http://en.wikipedia.org/wiki/Rayleigh_scattering


Raleigh ScatteringElastic scattering of light or other electromagnetic radiation by particles much smaller than the wavelength of the radiation.

http://en.wikipedia.org/wiki/Rayleigh_scattering


Temperature MeasurementsThe radiation that impinges on the IR camera lens comes from three differentsources. The camera receives radiation from the target object, plus radiationfrom its surroundings that has been reflected onto the object’s surface. Bothof these radiation components become attenuated when they pass throughthe atmosphere. Since the atmosphere absorbs part of the radiation, it willalso radiate some itself (Kirchhoff’s law). Given this situation, we can derive aformula for the calculation of the object’s temperature from a calibratedcamera’s output.



1. Emission from the object = Ɛ ∙ τ ∙ Wobj ,Where Ɛ is the emissivity of the object (unit?) τ is the transmittance of the atmosphere.

2. Reflected emission from ambient sources = (1 – Ɛ) ∙ τ ∙ Wamb, Where (1 – Ɛ) is the reflectance of the object. (It is assumed that the ambient temperature Tamb is the same for all emitting surfaces within the half sphere seen from a point on the object’s surface.)

3. Emission from the atmosphere = (1 – τ) ∙ Watm, where (1 – τ) is the emissivity of the atmosphere.

4. The total radiation power received by the camera can now be written:Wtot = Ɛ ∙ τ ∙ Wobj + (1 – Ɛ) ∙ t ∙ Wamb + (1 – τ) ∙ Watm,Where e is the object emissivity, τ is the transmission through the atmosphere, Tamb is the (effective) temperature of the object’s surroundings, or the reflected ambient (background) temperature, and Tatm is the temperature of the atmosphere.



1. Emission from the object = (Ɛobj) ∙ (τatm ∙ Wobj),Where Ɛobj is the emissivity of the object (unit?) τatm is the transmittance of the atmosphere, Wobj emitted energy fro the object.

2. Reflected emission from ambient sources = (1 – Ɛobj)∙(τatm ∙ Wamb), Where (1 – Ɛ) is the reflectance of the object. (It is assumed that the ambient temperature Tamb is the same for all emitting surfaces within the half sphere seen from a point on the object’s surface.), Wamb emitted energy of ambient source.

3. Emission from the atmosphere = (1 – τ) ∙ Watm, where (1 – τ) is the emissivity of the atmosphere, Watm emitted energy from the atmosphere.

4. The total radiation power received by the camera can now be written:Wtot = Ɛ ∙ τ ∙ Wobj + (1 – Ɛ) ∙ τ ∙ Wamb + (1 – τ) ∙ Watm,Where e is the object emissivity, τ is the transmission through the atmosphere, Tamb is the (effective) temperature of the object’s surroundings, or the reflected ambient (background) temperature, and Tatm is the temperature of the atmosphere.



absorbtion alpha (α), reflection Rho (ρ), transmission Tau (τ ), emissivity epsilon (Ɛ).


Wtot = Ɛobj ∙ τatm ∙ Wobj + (1 – Ɛobj) ∙ τatm ∙ Wamb + (1- τatm) ∙ Watm,

1 = τatm + Ɛatm ,where ρatm=0

1 = ρobj + Ɛobj ,where τobj=0

Reflection from ambientEmission from object Emission from atmosphere

Wobj

Wamb

Watm


To arrive at the correct target object temperature, IR camera softwarerequires inputs for the emissivity of the object, atmospheric attenuation andtemperature, and temperature of the ambient surroundings. Depending oncircumstances, these factors may be measured, assumed, or found fromlook-up tables.

Keywords:atmospheric attenuation (transmittance, τatm ?)



Chapter 2: IR Detectors For Thermographic ImagingIR CamerasThermographic imaging is accomplished with a camera that converts infrared radiation (IR) into a visual image that depicts temperature variations across an object or scene. The main IR camera components are a lens, a detector in the form of a focal plane array (FPA), possibly a cooler for the detector, and the electronics and software for processing and displaying images (Figure 2.1). Most detectors have a response curve that is narrower than the full IR range (900–14,000 nanometers or 0.9μm –14μm). Therefore, a detector (or camera) must be selected that has the appropriate response for the IR range of a user’s application. In addition to wavelength response, other important detector characteristics include sensitivity, the ease of creating it as a focal plane array with micrometer size pixels, and the degree of cooling required, if any.



In most applications, the IR camera must view a radiating object through the atmosphere. Therefore, an overriding concern is matching the detector’s response curve to what is called an atmospheric window. This is the range ofIR wavelengths that readily pass through the atmosphere with little attenuation. Essentially, there are two of these windows, one in the 2μm –5.6μm range, the short/ medium wavelength (SW/MW) IR band, and one in the 8μm – 14μm range, the long wavelength (LW) IR band. There are many detector materials and cameras with response curves that meet these criteria.

Keywords:Atmospheric window



Figure 2.1. Simplified block diagram of an IR camera



Quantum vs. Non-Quantum Detectors The majority of IR cameras have a microbolometer type detector, mainly because of cost considerations. Microbolometer FPAs can be created from metal or semiconductor materials, and operate according to non-quantum principles. This means that they respond to radiant energy in a way that causes a change of state in the bulk material (i.e., the bolometer effect). Generally, microbolometers do not require cooling, which allows compact camera designs that are relatively low in cost. Other characteristics of microbolometers are:

• Relatively low sensitivity (detectivity) • Broad (flat) response curve • Slow response time (time constant ~12 ms)

For more demanding applications, quantum detectors are used, which operate on the basis of an intrinsic photoelectric effect. These materials respond to IR by absorbing photons that elevate the material’s electrons to a higher energy state, causing a change in conductivity, voltage, or current. By cooling these detectors to cryogenic temperatures, they can be very sensitive to the IR that is focused on them.



They also react very quickly to changes in IR levels (i.e., temperatures), having a constant response time on the order of 1μs. Therefore, a camera with this type of detector is very useful in recording transient thermal events. Still, quantum detectors have response curves with detectivity that varies strongly with wavelength (Figure 2.2). Table 2.1 lists some of the most commonly used detectors in today’s IR cameras.



Figure 2.2. Detectivity (D*) curves for different detector materials



Quantum Well Infrared PhotodetectorA Quantum Well Infrared Photodetector (QWIP) is an infrared photodetector, which uses electronic inter subband transitions in quantum wells to absorb photons. The basic elements of a QWIP are quantum wells, which are separated by barriers. The quantum wells are designed to have one confined state inside the well and a first excited state which aligns with the top of the barrier. The wells are n-doped such that the ground state is filled with electrons. The barriers are wide enough to prevent quantum tunneling between the quantum wells. Typical QWIPs consists of 20 to 50 quantum wells. When a bias voltage is applied to the QWIP, the entire conduction band is tilted. Without light the electrons in the quantum wells just sit in the ground state. When the QWIP is illuminated with light of the same or higher energy as the inter subband transition energy, an electron is excited.

http://en.wikipedia.org/wiki/Quantum_well_infrared_photodetector


Quantum Well Infrared Photodetector

http://en.wikipedia.org/wiki/Quantum_well_infrared_photodetector


Bolometer Effect A bolometer, meaning measurer of thrown things is a device for measuring the power of incident electromagnetic radiation via the heating of a material with a temperature-dependent electrical resistance. It was invented in 1878 by the American astronomer Samuel Pierpont Langley. The name comes from the Greek word bole, for something thrown, as with a ray of light

Principle of operationA bolometer consists of an absorptive element, such as a thin layer of metal, connected to a thermal reservoir (a body of constant temperature) through a thermal link. The result is that any radiation impinging on the absorptive element raises its temperature above that of the reservoir — the greater the absorbed power, the higher the temperature. The intrinsic thermal time constant, which sets the speed of the detector, is equal to the ratio of the heat capacity of the absorptive element to the thermal conductance between the absorptive element and the reservoir.[2] The temperature change can be measured directly with an attached resistive thermometer, or the resistance of the absorptive element itself can be used as a thermometer. Metal bolometers usually work without cooling. They are produced from thin foils or metal films. Today, most bolometers use semiconductor or superconductor absorptive elements rather than metals. These devices can be operated at cryogenic temperatures, enabling significantly greater sensitivity.

Bolometers are directly sensitive to the energy left inside the absorber. For this reason they can be used not only for ionizing particles and photons, but also for non-ionizing particles, any sort of radiation, and even to search for unknown forms of mass or energy (like dark matter); this lack of discrimination can also be a shortcoming. The most sensitive bolometers are very slow to reset (i.e., return to thermal equilibrium with the environment). On the other hand, compared to more conventional particle detectors, they are extremely efficient in energy resolution and in sensitivity. They are also known as thermal detectors.


Conceptual schematic of a bolometer. Power P from an incident signal is absorbed by the bolometer and heats up a thermal mass with heat capacity C and temperature T. The thermal mass is connected to a reservoir of constant temperature through a link with thermal conductance G. The temperature increase is ΔT = P/G. The change in temperature is read out with a resistive thermometer. The intrinsic thermal time constant is τ = C/G.


In short: Bolometer Effect A bolometer, is a device for measuring the power of incident electromagnetic radiation via the heating of a material with a temperature-dependent electrical resistance.


Bolometer:The design of cosmic microwave background experiments is a very challenging task. The greatest problems are the receivers, the telescope optics and the atmosphere. Many improved microwave amplifier technologies have been designed for microwave background applications. Some technologies used are HEMT, MMIC, SIS and bolometers. Experiments generally use elaborate cryogenic systems to keep the amplifiers cool. Often, experiments are interferometers which only measure the spatial fluctuations in signals on the sky, and are insensitive to the average 2.7 K background.


Table 2.1. Detector types and materials commonly used in IR cameras.

The Kelvin is a unit of measure for temperature based upon an absolute scale. It is one of the seven base units in the International System of Units (SI) and is assigned the unit symbol K. The Kelvin scale is an absolute, thermodynamic temperature scale using as its null point absolute zero, the temperature at which all thermal motion ceases in the classical description of thermodynamics. The Kelvin is defined as the fraction 1⁄273.16 of the thermodynamic temperature of the triple point of water (exactly 0.01 °C or 32.018 °F). In other words, it is defined such that the triple point of water or approximately 0ºC is exactly 273.16 K



LW Photon Detector 77K.

http://www.pro-lite.uk.com/File/MCT_detectors.php

■ http://irassociates.com/index.php?page=hgcdte


Broad Band IR- The extended spectral area of an MWIR camera simplifies the spatial assignment of gas plumes to visible objects.

http://www.photonics.com/Article.aspx?AID=56861


MW Photon Detector 77K.

http://www.pro-lite.uk.com/File/InSb_detectors.php

■ http://irassociates.com/index.php?page=insb


InGaAs Detectors & Avalanche Photodiodes

Large area & high sensitivity from 800 to 2200nmPro-Lite offers Indium Gallium Arsenide (InGaAs) detectors and avalanche photodiodes (APD) from GPD Optoelectronics Corporation. InGaAs detectors operate from 800 to 1700nm and are similar to Ge but with enhanced sensitivites at low light levels. Available options include large area InGaAs (up to 5mm), custom packages and submounts, custom filters and windows, extended range InGaAs (to 2.2µm) and high speed InGaAs (up to 4GHz). GPD also produces InGaAs avalanche photodiodes (APD) with active areas of 80 and 200µm. An APD can be regarded as the semiconductor equivalent of the photomultiplier tube (PMT) detector. With the application of a reverse bias Voltage, an APD experiences a high internal current gain, making an avalanche photodiode significantly more sensitive to low light levels than a regular InGaAs detector. Our APDs can be supplied as chip/submount combinations, in TO-46 cases with flat windows or ball lenses and as fibre pigtailed packages.

http://www.pro-lite.uk.com/File/InGaAs_detectors.php


Germanium Detectors & Avalanche Photodiodes

Economical near-infrared detection from 800 to 1800nmPro-Lite offers Germanium (Ge) detectors and avalanche photodiodes (APDs) from GPD Optoelectronics Corporation. Gedetectors operate from 800 to 1800nm and are similar to InGaAs but have a reduced sensitivity, are more economical and provideimproved linearity at high levels of irradiance. Available options include active areas from 0.1 to 13mm diameter, two-coloursilicon/germanium (Si/Ge) detectors, cryogenic cooling (TE coolers & dewars), custom packages and submounts, custom filters and windows and avalanche Ge photodiodes.

http://www.pro-lite.uk.com/File/InGaAs_detectors.php


Operating Principles for Quantum DetectorsIn materials used for quantum detectors, at room temperature there areelectrons at different energy levels. Some electrons have sufficient thermalenergy that they are in the conduction band, meaning the electrons there arefree to move and the material can conduct an electrical current. Most of the electrons, however, are found in the valence band, where they do not carry any current because they cannot move freely. (See left-most views of Fig 2.3.) When the material is cooled to a low enough temperature, which varies with the chosen material, the thermal energy of the electrons may be so low that there are none in the conduction band (upper center view of Figure 2.3). Hence the material cannot carry any current. When these materials are exposed to incident photons, and the photons have sufficient energy, this energy can stimulate an electron in the valence band, causing it to move up into the conduction band (upper right view of Figure 2.3).



Figure 2.3. Operating principle of quantum detectors



QWIP FPA mounted on a ceramic substrate and bonded to external electronics.



Thus the material (the detector) can carry a photocurrent, which is proportional to the intensity of the incident radiation. There is a very exact lowest energy of the incident photons that will allow an electron to jump from the valence band into the conduction band. This energy is related to a certain wavelength, the cutoff wavelength. Since photon energy is inversely proportional to its wavelength, the energies are higher in the SW/MW band than in the LW band. Therefore, as a rule, the operating temperatures for LW detectors are lower than for SW/MW detectors. For an InSb MW detector, the necessary temperature must be less than 173 K (–100°C), although it may be operated at a much lower temperature. An HgCdTe (MCT) LW detector must be cooled to 77 K (–196°C) or lower. A QWIP detector typically needs to operate at about 70 K (–203°C) or lower. The lower center and right views of Figure 3 depict quantum detector wavelength dependence. The incident photon wavelength and energy must be sufficient to overcome the band gap energy, ΔE.



Cooling MethodsThe first detectors used in infrared radiometric instruments were cooled with liquid nitrogen. The detector was attached to the Dewar flask that held the liquid nitrogen, thus keeping the detector at a very stable and low temperature (-196°C). Later, other cooling methods were developed. The first solid-state solution to the cooling problem was presented by AGEMA in 1986, when it introduced a Peltier effect cooler for a commercial IR camera. In a Peltiercooler, DC current is forced through a thermoelectric material, removing heat from one junction and creating a cold side and a hot side. The hot side is connected to a heat sink, whereas the cold side cools the component attached to it.

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Cooling MethodsThe first detectors used in infrared radiometric instruments were cooled with liquid nitrogen. The detector was attached to the Dewar flask that held the liquid nitrogen, thus keeping the detector at a very stable and low temperature (-196°C). Later, other cooling methods were developed. The first solid-state solution to the cooling problem was presented by AGEMA in 1986, when it introduced a Peltier effect cooler for a commercial IR camera. In a Peltier cooler, DC current is forced through a thermoelectric material, removing heat from one junction and creating a cold side and a hot side. The hot side is connected to a heat sink, whereas the cold side cools the component attached to it. See Figures 2.4 and 2.5.

For very demanding applications, where the highest possible sensitivity was needed, an electrical solution to cryogenic cooling was developed. This resulted in the Stirling cooler. Only in the last 15 to 20 years were manufacturers able to extend the life of Stirling coolers to 8,000 hours or more, which is sufficient for use in thermal cameras.The Stirling process removes heat from the cold finger (Figure 2.6) and dissipates it at the warm side. The efficiency of this type of cooler is relatively low, but good enoughfor cooling an IR camera detector. Regardless of the cooling method, the detector focal plane is attached to the cold side of the cooler in a way that allows efficient conductive heat exchange. Because focal plane arrays are small, the attachment area and the cooler itself can be relatively small.



Figure 2.4. Single stage Peltier cooler



Figure 2.5. Three-stage Peltier cooler



Figure 2.6. Integrated Stirling cooler, working with to external electronicshelium gas, cooling down to -196 ºC or sometimes even lower temperatures



Focal Plane Array AssembliesDepending on the size/resolution of an FPA assembly, it has from (approximately)60,000 to more than 1,000,000 individual detectors. For the sake of simplicity, this can be described as a two-dimensional pixel matrix with each pixel (detector) having micrometer size dimensions. FPA resolutions can range from about 160 × 120 pixels up to 1024 × 1024 pixels. In reality, assemblies are a bit more complex. Depending on the detector material and its operating principle, an optical grating may be part of the FPA assembly. This is the case for QWIP detectors, in which the optical grating disperses incident radiation to take advantage of directional sensitivity in the detector material’s crystal lattice. This has the effect of increasing overall sensitivity of a QWIP detector. Furthermore, the FPA must be bonded to the IR camera readout electronics. A finished QWIP detector and IC electronics assembly is shown in Figure 8. This would be incorporated with a Dewar or Stirling cooler in an assembly similar to those shown in Figure 7. Another complexity is the fact that each individual detector in the FPA has a slightly different gain and zero offset. To create a useful thermographic image, the different gains and offsets must be corrected to a normalized value. This multi-step calibration process is performed by the camera software. See Figures 2.9 –2.11. The ultimate result is a thermographic image that accurately portrays relative temperatures across the target object or scene (Figure 2.12). Moreover, actual temperatures can be calculated to within approximately ±1°C accuracy.



Figure 2.7. Examples of cooled focal plane array assemblies used in IR cameras



Figure 2.8. QWIP FPA mounted on a ceramics substrate and bonded to external electronics



Figure 2.9. To normalize different FPA detector gains and offsets, the first correction step is offset compensation. This brings each detector responsewithin the dynamic range of the camera’s A/D converter electronics.



Figure 2.10. After offset compensation, slope correction is applied.



Figure 2.11. After gain factors are brought to the same value, non-uniformity correction (NUC) is applied so that all detectors have essentially the same electronic characteristics.



Figure 2.12. IR image from a 1024 × 1024 InSb detector camera (MW PD)



High-end InSb cameras ImageIR ® 8300/9300 Z for long-range identification

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Application CriteriaAs indicated earlier, different types of detectors have different thermal andspectral sensitivities. In addition, they have different cost structures due tovarious degrees of manufacturability. Where they otherwise fit the application,photon detectors such as InSb and QWIP types offer a number of advantages:

• High thermal sensitivity• High uniformity of the detectors, i.e., very low fixed pattern noise• There is a degree of selectability in their spectral sensitivity• High yield in the production process• Relatively low cost• They are resistant to high temperatures and high radiation• They produce very good image quality



Camera electronics can handle wide variations in absolute detector sensitivities. For example, high sensitivity that might saturate a detector at high thermal intensities can be handled by aperture control and neutral density filters. Both of these solutions can reduce the radiant energy impinging on the FPA.

Price aside, spectral sensitivity is often an overriding concern in selecting a detector and camera for a specific application. Once a detector is selected, lens material and filters can be selected to somewhat alter the overall response characteristics of an IR camera system. Fig 2.13 shows the system response for a number of different detectors.



Figure 2.13. Relative response curves for a number of IR cameras



Chapter 3: Getting The Most From Your IR CameraUnderstanding IR camera calibration and corrections help ensure accurate temperature measurements and thermographic mapping.

Quantitative Measurements with IR CamerasFor best results, IR camera users need to think carefully about the type of measurements they need to make, and then be proactive in the camera’s calibration process. Of course, the first step is selecting a camera with the appropriate features and software for the application. An understanding of the differences between (1) thermographic and (2) radiometric measurements is very helpful in this regard.

Thermography is a type of infrared imaging in which IR cameras detect radiation in the electromagnetic spectrum with wavelengths from roughly 900 to 14,000 nanometers (0.9 μm –14 μm ) and produce images of that radiation.Typically, this imaging is used to measure temperature variations across an object or scene, which can be expressed in degrees Celsius, Fahrenheit, or Kelvin.



Radiometry is the measurement of radiant electromagnetic energy,especially that associated with the IR spectrum. It can be more simply defined as an absolute measurement of radiant flux. The typical unit of measure for imaging radiometry is radiance, which is expressed in units of Watts/(sr-cm2). (The abbreviation “sr” stands for steradian; a non-dimensional geometric ratioexpressing the solid (conical) angle that encloses a portion of the surface of a sphere equivalent to the square of the radius.)

In simple terms, one can think of thermography as “how hot” an object is, whereas radiometry is “how much energy” the object is giving off.

Although these two concepts are related, they are not the same thing. IR cameras inherently measure irradiance not temperature, but thermography does stem from radiance. When you thermographically calibrate an IR system you are calibrating /measuring based on effective blackbody radiance and temperature. Therefore, the emissivity of the target object you are measuring is vital to achieving accurate temperatures. (Emissivity or emittance is the radiative property of an object relative to a perfect blackbody.)



Entry level IR cameras with microbolometer detectors operate according tonon-quantum principles. The detectors respond to radiant energy in a waythat causes a change of state in the bulk material (e.g., resistance orcapacitance). Calibration software in these cameras is oriented towardthermographic imaging and temperature measurements. High end IR cameras with photon detectors operate according to quantum physicsprinciples. Although they also provide high quality images, their software is typically more sophisticated, allowing accurate measurements of both radiance and temperature.



Some reasons why radiance measurements are important include:1. Given a linear sensor, measured radiance is linear with incident energy.

Temperature is non-linear with raw digital image counts, even with a linear sensor.

2. Given the radiance and area of an object, radiant intensity can be calculated. Knowing total radiant intensity of a target gives a radiometric analyst the ability to model the irradiance generated by the target over various geometric and atmospheric conditions.

3. The relationship between spectral bands of interest can be much easier to determine if you are working within radiometric units.

4. The comparison between different objects in radiometric terms tends to have less uncertainty because emissivity is not a concern. (One still needs to consider atmospheric and spectral band-pass effects.)

5. One can typically convert a radiometric signature from radiance to effective blackbody temperature given a few assumptions or ancillary measurement data. It tends to be more difficult to go from temperature to radiance.



Key Physical Relationships in Camera OperationThere are five basic steps in producing radiometric and thermographicmeasurements with an IR camera system:

1. The target object has a certain energy signature that is collected by the IRcamera through its lens.

2. This involves the collection of photons in the case of a photon detector, orcollection of heat energy with a thermal detector, such as a microbolometer.

3. The collected energy causes the detector to produce a signal voltage that results in a digital count through the system’s A/D converter. (For example, a FLIR ThermoVisionR SC6000 IR camera has a 14-bit dynamic range in its A/D converter, which creates count values ranging from 0–16,383. The more IR energy incident on the camera’s detector (within its spectral band), the higher the digital count.)

4. When the camera is properly calibrated, digital counts are transformed into radiance values.

5. Finally, the calibrated camera‘s electronics convert radiance values to temperature using the known or measured emissivity of the target object.



Expanding on Steps 4 and 5, an effective blackbody temperaturemeasurement can be derived from a radiance measurement by applying aradiometric calibration, temperature vs. radiance model, and emissivity of thetarget object or scene. Every IR camera designed for serious measurementsis calibrated at the factory. In the calibration lab, the camera takes a numberof blackbody measurements at known temperatures, radiance levels,emissivities, and distances. This creates a table of values based on the A/Dcounts from the temperature/radiance measurements.

Once the counts for each blackbody temperature measurement are entered into the calibration software, the data are then passed through an in-band radiance curve fit algorithm to produce the appropriate in-band radiance vs. count values given the camera system’s normalized spectral response function. This produces a radiometric calibration of in-band radiance [W/(sr-cm2)] versus the digital counts obtained while viewing a blackbody over a range of temperatures. The result is a series of calibration curves. An example of how calibration points are captured is shown in Figure 3.1.



Figure 3.1. Example of camera measurements and corresponding in-band radiance values for given black body temperatures with resulting radiance vs. measurement curve.



The calibration curves are stored in the camera system’s memory as a seriesof numeric curve-fit tables that relate radiance values to blackbodytemperatures. When the system makes a measurement, it takes the digitalvalue of the signal at a given moment, goes into the appropriate calibrationtable, and calculates temperature. Due consideration is given to other factorslike atmospheric attenuation, reflected ambient temperature, and thecamera’s ambient temperature drift before the final result is presented.



Ambient Drift Compensation (ADC).Another important consideration in the calibration process is the radiation caused by the heating and cooling of the camera itself. Any swings in camera internal temperature caused by changes in environment or the heating and cooling of camera electronics will affect the radiation intensity at the detector. The radiation that results directly from the camera is called parasitic radiationand can cause inaccuracies in camera measurement output, especially with thermographically calibrated cameras. Certain IR cameras (like the FLIR ThermoVisionR product line), have internal sensors that monitor changes in camera temperature. As part of the calibration process, these cameras are placed in an environmental chamber and focused at a black body reference.

The temperature of the chamber and black body are then varied and data is collected from the internal sensors. Correction factors are then created and stored in the camera. In real-time operation, the camera sensors continually monitor internal temperature and send feedback to the camera processor. The camera output is then corrected for any parasitic radiation influences. This functionality is commonly referred to as ambient drift compensation.



Ultimately, the camera must calculate at an object’s temperature based on:

(1) its emission,(2) reflected emission from ambient sources, and (3) emission from the atmosphere

using the Total Radiation Law. The total radiation power received by the camera can be expressed as:

Wtot = Ɛ ∙ τ ∙ Wobj + (1 – Ɛ) ∙ τ ∙ Wamb + (1 – τ) ∙ Watm,

Where: Ɛ is the object emissivity, τ is the transmission through the atmosphere, Tambis the (effective) temperature of the object surroundings, or the reflected ambient (background) temperature, and Tatm is the temperature of the atmosphere.



The best results are obtained when a user is diligent in entering known values for allthe pertinent variables into the camera software. Emissivity tables are available for a wide variety of common substances. However, when in doubt, measurements should be made to obtain the correct values.

Calibration and analysis software tools available to users are not always containedonboard the camera. While high-end cameras have many built-in software functions, others rely on external software that runs on a PC. Even high-end cameras are connected to PCs to expand their internal calibration, correction, and analysis capabilities. For example, FLIR’s ThermaCAMR RTools™ software can serve a wide variety of functions from real-time image acquisition to post-acquisition analysis.

Whether the software is on the camera or an external PC, the most useful packages allow a user to easily modify calibration variables. For instance, FLIR’s ThermaCAMRTools provides the ability to enter and modify emissivity, atmospheric conditions, distances, and other ancillary data needed to calculate and represent the exact temperature of the object, both live and through saved data. This software provides a post-measurement capability to further modify atmospheric conditions, spectral responsivity, atmospheric transmission changes, internal and external filters, and other important criteria as needed. The discussions that follow below are intended to represent both onboard and external camera firmware and software functions. Where these functions reside depends on the camera.



Typical Camera Measurement Functions IR cameras have various operatingmodes to assure correct temperature measurements under differentapplication conditions. Typical measurement functions include:

• Spotmeter• Area• Profile• Isotherm• Temperature range• Color or gray scale settings

Cursor functions allow easy selection of an area of interest, such as the crosshairs of the spot readings in Figure 3.2. In addition, the cursor may be able to select circle, square, and irregularly shaped polygon areas, or create a line for a temperature profile. Once an area is selected, it can be “frozen” so that the camera can take a snapshot of that area. Alternatively, the camera image can remain live for observation of changes in temperature.



Figure 3.2. IR image of a printed circuit board indicating three spot temperature readings. Image colors correspond to the temperature scale on the right.



The spotmeter finds the temperature at a particular point. Depending on thecamera, this function may allow ten or more movable spots, one or more ofwhich may automatically find the hottest point in the image. The area functionisolates a selected area of an object or scene and finds the maximum,minimum, and average temperatures inside that area. The isotherm functionmakes it possible to portray the temperature distribution of a hot area.Multiple isotherms may be allowed. The line profile is a way to visualize thetemperature along some part of the object, which may also be shown as a graph (Figure 3.3).

Figure 3.3. Graph of temperature along a selected area of a target object using a camera’s profile function



The temperature measurement range typically is selectable by the user. Thisis a valuable feature when a scene has a temperature range narrower than acamera’s full-scale range. Setting a narrower range allows better resolution ofthe images and higher accuracy in the measured temperatures. Therefore,images will better illustrate smaller temperature differences. On the otherhand, a broader scale and/or higher maximum temperature range may beneeded to prevent saturation of the portion of the image at the highesttemperature. As an adjunct to the temperature range selection, most camerasallow a user to set up a color scale or gray scale to optimize the cameraimage.

Figure 3.4 illustrates two gray scale possibilities. In Figure 3.2 a so-called“iron scale” was used for a color rendering. In a manner similar to the grayscale used in Figure 4, the hottest temperatures can be rendered as eitherlighter colors or darker colors. Another possibility is rendering images withwhat is known as a rainbow scale (Figure 3.5). In some color images, gray isused to indicate areas where the camera detector has become saturated (i.e.,temperatures well above the top of the scale).



Figure 3.4. Gray scale images of car engine; left view has white as the hottest temperature; right view shows black as the hottest



Figure 3.5. Rainbow scale showing lower temperatures towards the blue end of the spectrum



While choice of color scale is often a matter of personal preference, theremay be times when one type of scale is better than another for illustrating therange of temperatures in a scene. In the case of isotherm measurements,areas with the same thermal radiance are highlighted. If we use a color scalewith ten colors, we will in fact get ten isotherms in the image. Such a scalesometimes makes it easier to see the temperature distribution over an object.

In Figure 3.6, the temperature scale is selected so that each color is anisotherm with a width of 2°C. Still, it is important to realize that an isothermaltemperature scale rendering will not be accurate (1) unless all of thehighlighted area has the same emissivity, and (2) the ambient temperatures are the same for all objects within the area. This points out common problems for IR camera users. Often, emissivity varies across an object or scene, along with variations in ambient temperatures, accompanied by atmospheric conditions that don’t match a camera’s default values. This is why IR cameras include measurement correction and calibration functions.



Figure 3.6. Isotherm color scale with each color having an isotherm width of 2°C



Emissivity CorrectionsIn most applications, the emissivity of an object is based on values found in atable. Although camera software may include an emissivity table, usersusually have the capability of inputting emissivity values for an object rangingfrom 0.1 to 1.0. Many cameras also provide automatic corrections based onuser input for reflected ambient temperature, viewing distance, relativehumidity, atmospheric transmission, and external optics. As described earlier,the IR camera calculates a temperature based on radiance measurementsand the object’s emissivity. However, when the emissivity value is unknownor uncertain, the reverse process can be applied. Knowing the objecttemperature, emissivity can be calculated. This is usually done when exactemissivity values are needed. There are two common methods of doing this.The first method establishes a known temperature by using an equalizationbox. This is essentially a tightly controlled temperature chamber withcirculating hot air. The length of time in the box must be sufficient to allow thewhole object to be at a uniform temperature. In addition, it is absolutelynecessary that the object stabilize at a temperature different from thesurroundings where the actual measurements will take place. Usually, theobject is heated to a temperature at least 10°C above the surroundings toensure that the thermodynamics of the measurements are valid.



Once the object has reached the set temperature, the lid is drawn off and athermogram is captured of the object. The camera and/or software forprocessing thermograms can be used to get the emissivity value.

Another (“adjacent spot”) method is much simpler, but still gives reasonably exact values of the emissivity. It uses an area of known emissivity. The idea is to determine the temperature of the object with the camera in the usual way.The object is adjusted so that the area with unknown emissivity is very closeto an area of known emissivity. The distance separating these areas must beso small that it can be safely assumed they have the same temperature. Fromthis temperature measurement the unknown emissivity can be calculated.

The problem is illustrated in Figure 7, which is an image of a printed circuitboard (PCB) heated to a uniform temperature of 68.7°C. However, areas ofdifferent emissivities may actually have different temperatures, as indicated inthe caption of Figure 3.7a. Using the technique just described, emissivitycorrection proceeds by finding a reference spot where a temperature of68.7°C is indicated and calculating the emissivity at that location. By knowingthe emissivity of the reference spot, the emissivity of the target spots can becalculated. The corrected temperatures are shown in Figure 3.7b.



Figure 3.7a. PCB heated to a uniform 68.7°C, but digital readouts are incorrect.



Figure 3.7b. PCB with emissivity correction using the “adjacent spot”technique. Digital readouts now indicate the correct temperatures at alllocations.



As illustrated in these figures, this technique can be used with a camera’sarea selection function (“AR” in the figures) and using the averagetemperature for that area. The reason for using the average temperature inthe reference area is that there is usually a spread of temperatures within thearea, especially for materials with low emissivity. In that case, using a spotmeter or an area maximum value would give a less stable result. The isotherm function is not recommended either, as it is not possible to get the averaging effect with it. It may also be possible to use a contact sensor to find the temperature of an area of unknown emissivity, but such measurements pose other problems that may not be easy to overcome.

Furthermore, it is never possible to measure the emissivity of an object whose temperature is the same as the reflected ambient temperature from its surroundings. Generally, a user can also input other variables that are needed to correct for ambient conditions. These include factors for ambient temperatures and atmospheric attenuation around the target object.



Using Camera Specifications When considering IR camera performance,most users are interested in how small an object or area can be detected andaccurately measured at a given distance. Knowing a camera’s field of view(FOV) specifications helps determine this.

Field of View (FOV). This parameter depends on the camera lens and focal plane dimensions, and is expressed in degrees, such as 35.5° × 28.7° or 18.2 × 14.6°. For a given viewing distance, this determines the dimensions of the total surface area “seen” by the instrument (Figure 3.8). For example, a FLIR ThermoVision SC6000 camera with a 25mm lens has an FOV of 0.64 ×0.51 meters at a distance of one meter, and 6.4 × 5.1 meters at a distance of ten meters.



Figure 3.8. A camera’s field of view (FOV) varies with viewing distance.



Instantaneous Field of View (IFOV). This is a measure of the spatial resolution of a camera’s focal plane array(FPA) detector. The configuration of the FPA in the FLIR ThermoVisionSC6000 is 640 × 512 detectors, which makes a total of 327,680 individualpicture elements (pixels). Suppose you are looking at an object at a distanceof one meter with this camera. In determining the smallest detectable object,it is important to know the area’s IFOV covered by an individual pixel in thearray. The total FOV is 0.64 × 0.51 meters at a distance of one meter. If we divide these FOV dimensions by the number of pixels in a line and row, respectively, we find that a pixel’s IFOV is an area approximately 1.0 ×1.0mm at that distance. Figure 3.9 illustrates this concept.



Figure 3.9. A camera’s geometric (spatial) resolution (IFOV) is determined byits lens and FPA configuration.



To use this information consider, the pixel IFOV relative to the target objectsize (Figure 3.10). In the left view of this figure, the area of the object to bemeasured covers the IFOV completely. Therefore, the pixel will receiveradiation only from the object, and its temperature can be measured correctly.In the right view of Figure 3.10, the pixel covers more than the target object area and will pick up radiation from extraneous objects. If the object is hotter than the objects beside or behind it, the temperature reading will be too low, and vice versa. Therefore it is important to estimate the size of the target object compared to the IFOV in each measurement situation.

Figure 3.10. IFOV (red squares) relative to object size.



Spot Size Ratio (SSR).At the start of a measurement session, the distance between the camera andthe target object should be considered explicitly. For cameras that do nothave a calibrated spot size, the spot size ratio method can be used tooptimize measurement results. SSR is a number that tells how far the cameracan be from a target object of a given size in order to get a good temperaturemeasurement. A typical figure might be 1,000:1 (also written 1,000/1, orsimply abbreviated as 1,000). This can be interpreted as follows: at 1000 mmdistance from a target, the camera will measure a temperature averaged overa 1mm square. Note that SSR is not just for targets far away. It can be just asimportant for close-up work. However, the camera’s minimum focal distancemust also be considered. For shorter target distances, some manufacturersoffer close-up lenses.



For any application and camera/lens combination, the following equation applies:

D/S = SSR/1 (or more conveniently S = D/SSR)

Where:D is the distance from the camera to the target,S is smallest target dimension of interest, andSSR is the spot size ratio.

The units of D and S must be the same. When selecting a camera, keep in mind that IFOV is a good figure of merit to use. The smaller the IFOV, the better the camera for a given total field of view.



Other Tools for Camera UsersAs mentioned earlier, IR cameras are calibrated at the factory, and fieldcalibration in not practical. However, some cameras have a built-in blackbodyto allow a quick calibration check. These checks should be done periodicallyto assure valid measurements. Bundled and optional data acquisitionsoftware available for IR cameras allows easy data capture, viewing, analysis,and storage. Software functions may include real-time radiometric output ofradiance, radiant intensity, temperature, target length/area, etc. Optionalsoftware modules are also available for spatial and spectral radiometriccalibration空间与光谱辐射测量标定.

Functions provided by these modules might include:• Instrument calibration in terms of radiance, irradiance, and temperature• Radiometric data needed to set instrument sensitivity and spectral range• Use of different transmission and/or emissivity curves or constants for

calibration data points • Adjustments for atmospheric effects



In addition, IR camera software and firmware provide other user inputs thatrefine the accuracy of temperature measurements. One of the most importantfunctions is non-uniformity correction (NUC) of the detector FPA. This type ofcorrection is needed due to the fact that each individual detector in thecamera’s FPA has a slightly different gain and zero offset. To create a usefulthermographic image, the different gains and offsets must be corrected to anormalized value. This multi-step NUC process is performed by camerasoftware. However, some software allows the user to specify the manner inwhich NUC is performed by selecting from a list of menu options. Forexample, a user may be able to specify either a one-point or a twopointcorrection.

■ A one-point correction only deals with pixel offset.

■ Two-point corrections perform both gain and offset normalization of pixel- to-pixel nonuniformity.



With regard to NUC, another important consideration is how this function deals with the imperfections that most FPAs have as a result ofsemiconductor wafer processing. Some of these imperfections are manifestedas bad pixels that produce no output signals or as outputs far outside of acorrectable range. Ideally, the NUC process identifies bad pixels and replacesthem using a nearest neighbor replacement algorithm. Bad pixels areidentified based on a response and/or offset level outside user-defined pointsfrom the mean response and absolute offset level. Other NUC functions maybe included with this type of software, which are too numerous to mention.The same is true of many other off-the-shelf software modules that can bepurchased to facilitate thermographic image display, analysis, data filestorage, manipulation, and editing. Availability of compatible software is animportant consideration when selecting an IR camera for a user’s applicationor work environment.



ConclusionsRecent advances in IR cameras have made them much easier to use.Camera firmware has made setup and operation as simple as using aconventional video camera. Onboard and PC-based software providespowerful measurement and analysis tools. Nevertheless, for accurate results,the user should have an understanding of IR camera optical principals andcalibration methods. At the very least, the emissivity of a target object shouldbe entered into the camera’s database, if not already available as a tableentry.

Keywords:At the very least, the emissivity of a target object should be entered into the camera’s database, if not already available as a table entry.



Chapter 4: Filters Extend IR Camera Usefulness Where Filters Can HelpMaterials that are transparent or opaque to IR wavelengths present problems in non-contact temperature measurements with an IR camera. With transparent materials, the camera sees through them and records a temperature that is a combination of the material itself and that which is behind it. In the second case, when an IR camera needs to see through a material to measure the temperature of an object behind it, signal attenuation and ambient reflections can make accurate temperature readings difficult or impossible. In some cases, an IR filter can be placed in the camera’s optical path to overcome these problems.



IR Window: Cordex IR Window


Spectral Response is the KeyIR cameras inherently measure irradiance not temperature. However, acamera’s software coverts radiance measurements into temperatures byusing the known emissivity of a target object and applying internal calibrationdata for the camera’s spectral response. The spectral response is determinedprimarily by the camera’s lens and detector. Figure 4.1 shows the spectralresponse of a few IR cameras with various spectral responses. The spectralperformance of most cameras can be found in their user manual or technicalspecifications. For many objects, emissivity is a function of their radiancewavelength, and is further influenced by their temperature, the angle at whichthey are viewed by a camera, and other factors. An object whose emissivityvaries strongly with wavelength is called a selective radiator. One that has thesame emissivity for all wavelengths is called a greybody. Transparentmaterials, such as glass and many plastics, tend to be selective radiators. Inother words, their degree of transparency varies with wavelength. There maybe IR wavelengths where they are essentially opaque due to absorption.Since, according to Kirchhoff’s Law, a good absorber is also a good emitter,this opens the possibility of measuring the radiance and temperature of a selective radiator at some wavelength.



Figure 4.1. Relative response curves for a number of IR cameras



Spectral AdaptationInserting a spectral filter into the camera’s optical path is called spectraladaptation. The first step of this process is to analyze the spectral propertiesof the semitransparent material you are trying to measure. For commonmaterials the data may be available in published data. Otherwise, thisrequires analysis with a spectrophotometer. (The camera manufacturer or aconsulting firm may supply this service.) In either case, the objective is to findthe spectral location of a band of complete absorption that falls within the IRcamera’s response curve. Microbolometer detectors have rather broadresponse curves so they are not likely to present a problem in this respect.However, adding a filter decreases overall sensitivity due to narrowing of thecamera’s spectral range. Sensitivity is reduced approximately by the ratio ofthe area under the filter’s spectral curve to the area under the camera’sspectral curve.



This could be a problem for microbolometer systems, since they have relatively low sensitivity to start with and a broad spectral curve. Using a camera with, for example, a QWIP detector will provide greater sensitivity with a narrower spectral curve. Still, this narrow range may limit the application of such cameras for spectral adaptation. Ultimately, an optical (IR) filter must beselected that blocks all wavelengths except the band where the object absorbs. This ensures that the object has high emissivity within that band.Besides semitransparent solids, selective adaptation can also be applied to gases. However, a very narrow filter might be required for selecting an absorption “spike” in a gas. Even with proper filtering, temperaturemeasurement of gases is difficult, mainly due to unknown gas density.

Selective adaptation for a gas has a better chance of success if the objectiveis merely gas detection, since there are less stringent requirements forquantitative accuracy. In that case sensitivity would be more important, andsome gases with very high absorption might still be measurable.



Spectral adaptation could also be applied the opposite way, i.e., selection of a spectral band where the transmission through a medium is as high as possible. The purpose would be to enable measurement on an object by seeing through the medium without any interference. The medium could be ordinary atmosphere, the atmosphere of combustion gases inside a furnace, or simply a window (or other solid) through which one wants to measure.



Filter TypesThe simplest filters are broadband neutral density types that are used merelyto reduce optical transmission and prevent detector saturation at hightemperatures. While necessary sometimes, this is not spectral adaptation. Inspectral adaptation, filters are used in order to suppress or transmit certainwavelengths. For discussion purposes, filters can be described as short-pass(SP), long-pass (LP), band-pass (BP), and narrow band-pass (NBP). SeeFigure 4.2. SP and LP filters are specified with a cut-on and a cut-offwavelength. BP and NBP filters are specified with a center wavelength and a half-width (half-power) wavelength, the latter being the width where spectral response has decreased to 50% of its maximum. For temperature measurements on transparent materials, the filter selected must provide a band of essentially complete absorption. Incomplete absorption can be used, at least theoretically, provided that both absorptance and reflectance are known and stable at the absorption band. Unfortunately, absorption often varies with both temperature and thickness of the material.



Figure 4.2. Response curves for different types of filters



An example of applying a NBP filter to the measurement of polyethylene filmtemperature is shown in Figure 4.3. The blue curve in the figure shows theabsorption band of polyethylene film. The red curve shows the transmittanceof a 3.45μm NBP filter, which is designed to match polyethylene film. Thegreen curve shows the resulting transmission through film plus the filter. Thiscurve, running just above the zero line, indicates an excellent filter adaptation,i.e. the film appears to be opaque to the camera, and no background radiationwould disturb the measurement of film temperature. Filters can also beclassified according to their application temperature. Traditionally, cold filters,filters that are stabilized at or near the same temperature as the detector, arethe most accurate and desired filters for thermal signatures. Warm filters,filters screwed onto the back of the optical lens outside of the detector/coolerassembly, are also commonly used but tend to provide more radiometriccalibration uncertainty due to varying IR emission with ambient temperaturechanges. Once a filter is selected for use with a particular camera, the camera/filter combination needs to be calibrated by the camera manufacturer. Then the performance of the system should be characterized since accuracy and sensitivity will be affected due to a reduction in energy going to the detector.



Figure 4.3. Application of an NBP filter to achieve nearly complete absorption and high emittance from polyethylene film, allowing its temperature measurement



Transparent Material Measurement TechniquesProduction of sheet glass and thin plastic film requires fairly tight temperaturecontrol to maximize production quality and yield. Traditionally, temperaturesensors have been embedded at the orifice of the extruder, which providesrather coarse information about sheet/film temperature. An IR machine visionsystem can make noncontact temperature measurements and supply moreusable data about the material as it is extruded. However, as described above,an appropriate filter is needed for the IR camera to make the material appearopaque. To ensure that the proper filter was selected, spectral responsecurves for the camera/filter system can be created by the cameramanufacturer. (See the green curve in Figure 4.3.) In fact, this is generallyrequired for permanent cold filter installations to validate filter response.Otherwise, (with supportive spectral data) the user can proceed by checkingemissivity. This is a verification of emissivity efficiency for the overall systemresponse, including the target material and camera with installed filter.



Recalling Kirchhoff’s law,

ρλ + Ɛλ + τλ = 1, or Ɛλ = 1 – τλ – ρλ

it is clear that in order to get an emissivity value Ɛ, transmittance τ andreflectance ρ at the pass band of the filter must be known. The transmittance, τλ, can be taken directly from a transmission diagram like the one in Figure 3 (a value of about 0.02 in that example).

Where:absorbtion alpha (α),reflection Rho (ρ),transmission Tau (τ ),emissivity epsilon (Ɛ).



Reflectance is less easy to characterize and usually is a function of materialthickness. However, a transmission diagram like the one in Figure 4.4 provides some indication of this parameter’s value. Using the blue curve for the thinnest polyethylene material in Figure 4, which has the lowest absorption, the transmission between absorption bands is seen to be approximately 90%. If there were no absorption bands at all, we could conclude that the reflection would be 10%. Since there are some narrowabsorption bands under the curve, we can estimate the reflection to be 8% inthe spectral regions where absorption is very low. However, we are interested in the reflectance where the absorption is high (i.e., where the material appears to be opaque). To estimate the reflectance of this polyethylene film, we must first make the reasonable assumption that its surface reflectance stays constant over the absorption bands. Now recognize that the 8% value is the result of reflections from both sides of the film, i.e., approximately 4% per surface.



Figure 4.4. Transmission bands for polyethylene films of three different thicknesses



At the absorption band, however, since the absorption in the material is almost complete, we get reflection only on one side. Thus ρλ = 0.04.From this ρλ, and the τλ value obtained from the transmission graph (Figure 3 in this example), emissivity can be calculated: Ɛλ = 1 – 0.02 – 0.04 = 0.94.

This value is entered into the camera’s measurement database before having it calculate the temperatures from radiance observations. Sheet and plate glass production have similar temperature measurement requirements. The most common industrial varieties are variations of soda-lime- silica glass. Although they may vary in composition and color, their spectral characteristics do not change much. Looking at the spectral transmittance of such a glass with different thicknesses (Figure 4.5), one can conclude that IR temperature measurement must be restricted to wavelengths above 4.3μm. Depending on glass thickness, this may require either a mid wavelength (MW) or long wavelength (LW) camera/detector. MW cameras cover some portion of the spectrum from 2μm – 5μm, and LW cameras cover some portion within 8μm – 12μm.



Figure 4.5. Transmission curves for a common industrial glass in five thicknesses from 0.23mm to 5.9mm



In selecting a filter, the temptation might be to go for an LP type with a cut-onwavelength near the point where transmittance drops to zero. However, thereare other factors to consider. For example, LP filter characteristics caninterfere with the negative slope of the spectral response curve of thermo-lectrically cooled HgCdTe (MCT) detectors, which are used in both MW andLW cameras. A better choice may be a NBP filter. In Figure 4.6, transmissioncharacteristics of a glass, an SW camera, and two filters are superimposed.The green curve represents the LP filter response curve, whereas the NBPfilter response is shown in blue. The latter was selected for the spectrallocation where glass becomes “black,” and has a center wavelength of 5.0μm.



Figure 4.6. Two alternative filters for glass measurement with a SW camera



The reflectance of this glass is shown in Figure 4.7. Note the peak between 8and 12 μm, which must be avoided when using an LW camera to measure the glass. Another consideration is the camera’s viewing angle, because glass reflectance can change with angle of incidence. Fortunately reflectance does not change much up to an angle of about 45° relative to normal incidence (Figure 4.8). From Figure 4.8, a value 0.025 for the glassreflectance is valid when using either the 4.7μm LP or the 5.0μm NBP filter (Figure 4.6), because they both operate in the 5μm region. Consequently a proper value for the glass emissivity in those cases would be 1 – 0.025 = 0.975.



Figure 4.7. Reflectance of a common glass at normal (perpendicular) incidence



Figure 4.8. Glass reflectance as a function of camera viewing angle relative to normal incidence



Transmission Band ApplicationsFor many applications, the user will need to find a spectral band where themedium through which the camera is looking has minimum influence on themeasurement. The object of interest is at the end of a measurement path onthe other side of the medium. The medium is in most cases ordinary atmosphere, but it could also be a gas or a mixture of gases (e.g., combustion gases or flames), a window, or a solid semitransparent material. As is the case in absorption band applications, a spectral transmission measurement of the actual medium would be the ideal starting point. The objective is to find a band within the camera’s response curve where the medium has minimum influence on IR transmission from the target object. However, it is often impractical to perform such a measurement, particularly for gases at high temperatures. In such cases it may be possible to find the spectral properties of gas constituents (or other media) in IR literature, revealing a suitable spectrum for the measurement.



In most cases, IR camera manufacturers have anticipated the atmosphericattenuation problem. Camera manufacturers typically add a filter that reducesmeasurement errors due to inaccurate and/or varying atmosphericparameters by avoiding absorption bands of the constituent gases and watervapors. This is especially needed at long measurement distances and shorterwavelengths. For MW cameras, an appropriate filter utilizes the atmosphericwindow between the absorption bands of H2O+CO2 around 3μm or CO2 at4.2μm. Atmospheric effects on an LW camera are much less, since theatmosphere has an excellent window from 8μm to 12μm. However, cameras with a broad response curve reaching into the MW spectrum may require an LP filter. This is particularly true for high temperature measurements wherethe radiation is shifted towards shorter wavelengths and atmospheric influence increases. An LP filter with a cut-on at 7.4 μm blocks the lower part of the camera’s response curve.



An interesting transmission band application is temperature measurementson a gas-fired furnace, oven, or similar heating equipment. Objectives couldbe the measurement of flame temperature or the measurement of internal components through the flames. In the latter case, an unfiltered IR camera will be overwhelmed by the intense radiation from the flames, making measurement of the much weaker radiation from internal objects impossible. On the other hand, any transmission through the flames from cooler internal objects will make flame temperature measurements inaccurate. The flame absorption spectrum in Figure 4.9 reveals the spectral regions where these two types of measurement could be made. There is very little radiation from the flames in the 3.9 μm area, whereas there is a lot of radiation between the 4.2 and 4.4μm range. The idea is to employ filters that utilize these spectral windows for the desired measurements.



Figure 4.9. Flame absorption spectrum of a gas-fired furnace with two types for filters for different measurement applications



For measurement of internal components, you need to avoid strongabsorption bands because they attenuate the radiation from the target objectand they emit intensely due to the high gas temperature, thus blinding thecamera. Although gas-fired combustion gases consist mostly of CO2 andwater vapor, an atmospheric filter is unsuitable because gas concentrationsand temperatures are much higher. This makes the absorption bands deeperand broader. A flame filter is needed for this application. See Figure 9. This isa BP filter transmitting between 3.75 μm and 4.02 μm. With this filter installed, the camera will produce an image where the flames are almost invisible andthe internal structure of the furnace is presented clearly (Figure 10).

To get the maximum temperature of the flames, a CO2 filter will show they are as high as 1400°C. By comparison, the furnace walls as seen with the flame filter are a relatively cool 700°C.



Figure 4.10. FLIR ThermaCAM?image of furnace tubes with flame filter toallow accurate temperature measurement



ConclusionsFilters can extend the application of IR cameras into areas that mightotherwise restrict their use. Still, some preliminary spectrophotometermeasurements may be needed on the objects and media of interest if spectralinformation cannot be found in IR literature. Once a filter is selected andinstalled, the camera/filter system should be calibrated by the cameramanufacturer. Even with a well-calibrated system, it is a good idea to avoiderrors by not using spectral regions of uncertain or varying absorption relativeto the camera/ filter system response spectrum.



Infrared Filter


Chapter 5: Ultra High-Speed ThermographyRecent Advances in Thermal ImagingWe have all seen high-speed imagery at some point in our lives, be it a video of a missile in flight or a humming bird flapping its wings in slow motion. Both scenarios are made possible by high-speed visible cameras with ultra short exposure times and triggered strobe lighting to avoid image blur, and usually require high frame rates to ensure the captured video plays back smoothly. Until recently, the ability to capture high-speed dynamic imagery has not been possible with traditional commercial IR cameras. Now, recent advances in IR camera technologies, such as fast camera detector readouts and high performance electronics, allow high-speed imagery.



Challenges prohibiting high-speed IR cameras were based primarily on readout electronic designs, camera pixel clocks, and backend data acquisition systems being too slow. Older readout designs only allowed minimum integration times down to about 10μs, which in some cases were insufficient to stop motion on a fast moving target without image blur. Similarly, targets with very fast temperature changes could not be sampled at an adequate frame rate to accurately characterize the object of interest. Even with the advent of faster IR cameras, there still remains the hurdle of how to collect high resolution, high-speed data without overwhelming your data collection system and losing frames of data. Not all challenges for high-speed IR cameras were due to technology limitations.

Some were driven by additional requirements that restricted the maximum frame rates allowed. For example, cameras that required analog video output naturally restricted the maximum frame rate due to the NTSC and PAL format requirements of 30Hz or 25Hz, respectively. This is true regardless of the detector focal plane array’s (FPA) pixel rate capabilities, because the video monitor’s pixel rates are set by the NTSC or PAL timing parameters (vertical and horizontal blanking periods). However, with new improvements in high-end commercial R&D camera technologies, all these challenges have been overcome and we can begin exploring the many benefits of high-speed IR camera technology. The core benefits are the ability to capture fast moving targets without image blur, acquire enough data to properly characterize dynamic energy targets, and increase the dynamic range without compromising the number of frames per second.



Reducing Image Blur with Short Integration TimesWith advanced FPA Readout Integrated Circuits (ROIC), IR cameras canhave integration times (analogous to exposure time or shutter speed in visiblecameras) as short as 500ns. In addition, new ROIC designs maintain linearityall the way to the bottom of their integration time limits; this was not true forROICs developed only a few years ago. The key benefit again is to avoidmotion blur as the target moves or vibrates through the field of view of thecamera. With sub-microsecond integration times, these new cameras aremore than sufficient for fast moving targets such as missiles or in the following example, a bullet in flight.



Faster Than a Speeding BulletIn the following experiment, a high speed IR Camera was used to capture andmeasure the temperature of a 0.30 caliber rifle bullet in flight. At the point of image capture the bullet was traveling at supersonic speeds (800–900 meters per second) and was heated by friction within the rifle barrel, the propellant charge, andaerodynamic forces on the bullet. Due to this heat load, the IR camera could easily see the bullet even at the very short integration time of 1μs; so unlike a visible camera, no strobe source is needed. A trigger was needed to start the camera integration time to ensure the bullet was in the Field of View (FOV) of the camera at the time of frame capture. This was done by using an acoustic trigger from the rifle shot, which locates the bullet along the axis of fire to within a distance of several centimeters. Figure 5.1a shows a close-up IR image of the bullet traveling at 840m/s (~ 1900 mph); yet using the 1μs integration time, effectively reduced the image blur to about 5 pixels. Figure 5.1b shows a reference image of an identical bullet imaged with a visible light camera set to operate with a 2-microsecond integration time.

The orientation of the bullets in the two images is identical – they both travel from left to right. The bright glow seen on the waist of the image is a reflection of bright studiolights that were required to properly illuminate the bullet during the exposure. Unlike the thermal image, the visible image required active illumination, since the bullet was not hot enough to glow brightly in the visible region of the spectrum.



Figure 5.1a. Infrared image of a 0.30 caliber bullet in flight with apparent temperatures



Figure 5.1b. Visible-light image of an identical 0.30 caliber bullet in flight



High-Speed Imaging for Fast TransientsShort integration times and high-speed frame rates are not always pairedtogether in IR cameras. Many cameras have fast frame rates but not fastintegration times or vice versa. Still, fast frame rates are critical for properly characterizing targets whose temperatures change very quickly. An application where both short integration time and fast frame rate are required is overload testing of integrated circuits (ICs). See Figure 5.2. The objective of this test is to monitor the maximum heat load the IC experiences when biased and reverse biased with current levels outside the design limits. Without high-peed IR technology, sufficient data might not be captured to characterize the true heat transients on the IC due to under sampling. This would not only give minimal data to analyze, but could also give incorrect readings of the true maximum temperature. When the IC was sampled at a frame rate of 1000Hz, a maximum temperature of 95°C was reported. However, when sampled at only 500Hz, the true maximum temperature was missed and a false maximum of 80°C was reported (Figure 5.3). This is just one example of why high-speed IR cameras can be so valuable for even simple applications that don’t necessarily appear to benefit from high speed at first consideration.



Figure 5.2. Integrated circuit with 800ms overcurrent pulse



Figure 5.3. Maximum IC temperature data – actual vs. undersampled



Pixel Clock vs. Analog to Digital TapsHigh-speed IR cameras require as a prerequisite a combination of a fast pixelclock and a higher number of analog to digital (A/D) converters, commonlycalled channels or taps. As a frame of reference, most low performancecameras have two channels or A/D converters and run at lower than 40megapixels/second clock rates. This may sound fast, but when you considerthe amount of data, that translates into around 60Hz in most cases. High-peed IR cameras on the other hand typically have a minimum of fourchannels and have clock speeds of at least 50 megapixels/second. In turnthey offer 14-bit digital data at frame rates of over 120Hz at 640 × 512window sizes. In order to increase frame rates further, IR cameras usuallyallow the user to reduce the window size or number of pixels read out fromFPA. Since there is less data per frame to digitize and transfer, the overallframe rate increases. Figure 5.4 illustrates the increase in frame rates relativeto user defined window sizes. Newer camera designs offer 16 channels and pixel clocks upwards of 205 mega pixels/second. This allows for very fast frame rates without sacrificing the window size and overall resolution.



Figure 5.4. Example of FPA window sizes relative to frame rates



Preset Sequencing Increases Dynamic RangeHigh-speed IR cameras have an additional benefit that does not relate tohighspeed targets, but rather to increasing the dynamic range of the camera.By coupling a high-speed IR camera with a data capture method known assuperframing, you can effectively increase the camera’s dynamic range from14 bits to around 18 bits – 22 bits per frame. Superframing involves cycling the IR camera through up to four multiple integration times (presets), capturing one frame at each preset. This results in multiple unique data movie files, one for each preset. This data is then combined by using off-the-shelf ABATER software. The software selects the best resolved pixel from eachunique frame to build a resultant frame composed of data from all the collected data movie files at varying integration times. This method is especially beneficial for those imaging scenes with both hot and cold objects in the same field of view. Typically a 14-bit camera cannot imagesimultaneously both hot and cold objects with a single integration time. This would result in either over exposure on the hot object or under exposure on the cold object. The results of superframing are illustrated in the Beechcraft King Air aircraft images in Figure 5.5, captured at two different integration times.



Figure 5.5. Active aircraft engine imaged at integration rates of 2ms (left) and 30μs (right)



While the aircraft can be clearly seen in the left image (Preset 0 = 2msintegration time), there are portions of the engine that are clearly overexposed. Conversely, the right image in Figure 5.5 (Preset 1 = 30μs integration time), shows engine intake and exhaust detail with the remainder of the aircraft underexposed. When the two images in Figure 5.5 areprocessed in ABATER software, the best resolved pixels are selected and used to build a single resultant superframed image with no over or under exposed pixels (Figure 5.6). As you may have figured out, the down side to this method of data collection and analysis is the reduction in the frame rate by the number of Presets cycled. By applying some simple calculations a 100Hz camera with two Presets will provide an overall frame rate of 50Hz, well under the limits of our discussion of high speed IR imagery. This only reinforces the need for a high speed camera. If a 305Hz camera is superframed as in the example above, a rate of over 150Hz per preset frame rate is achieved. This rate is well within the bounds of high speed IR imaging.



Figure 5.6. Superframed image created with ABATER software from Preset 0 and Preset 1 data.



ConclusionsSophisticated IR cameras are now available with advanced readoutelectronics and high speed pixel clocks, which open the door for high speedIR imagery. This allows us to expand the boundaries of which applicationscan be solved using IR camera solutions. Furthermore, it allows us to begincapturing more data and increase our accuracy for demanding applicationswith fast moving targets, quick temperature transients, and wide dynamicrange scenes. With the release of this new technology in the commercial IR marketplace, we can now begin to realize the benefits of high speed datacapture, once only available to the visible camera realm.



A wide range of thermal imaging cameras for R&D and Science applicationsFLIR markets a full product range of thermal imaging cameras for R&D applications. Whether you are just discovering the benefits that thermalimaging cameras have to offer or if you are an expert thermographer, FLIRoffers you the correct tool for the job. Discover our full product range and findout why FLIR is the world leader for thermal imaging cameras.


Charlie Chong/ Fion Zhang http://www.flirmedia.com/MMC/THG/Brochures/T559243/T559243_EN.pdf


Software for demanding thermal imaging professionalsAt FLIR, we recognize that our job is to go beyond just producing the best possible infrared camera systems. We are committed to enabling all users of our thermal imaging camera systems to work more efficiently and productively by providing them with the most professional camera-software combination. Our team of committed specialists are constantly developing new, better and more user-friendly software packages to satisfy the most demanding thermalimaging professionals. All software is Windows-based, allows fast, detailed and accurate analysis and evaluation of thermal inspections.

For more information on FLIR products or software please contact your nearest FLIR representative of visit www.flir.com



Reading 2MWIR for Remote Sniffing and Locating of Gases



A mid-wave infrared camera visualizes methane gas leaking from a drilling platform.

Methane is a greenhouse gas that is significantly more damaging than carbon dioxide. When it leaks uncontrolled from industrial plants, it can easily escape into the atmosphere. This is seen primarily as an economic loss, but it also contributes to the destruction of the environment. Sensitive high-resolution mid-wave infrared (MWIR) cameras can accurately detect such emissions without placing a direct-measurement gas-detection system in the danger zone.

Raf Vandersmissen, Sinfrared, and Thomas Zimmermann, TIB Infrared Solutions



Figure 1. The transmission spectrum of methane (CH4) shows a strong attenuation between 3.3 and 3.6 µm and at a wavelength of 7.6 µm.



Gas leaking from a drilling platform A March 2012 incident on the Elgin Wellhead gas drilling platform in the

North Sea focused public attention on the risk connected with offshore mining of oil and gas.1 Elgin Wellhead (Figure 2) is one of more than 400 rigs in the North Sea, and it is a significant part of the exploration of the Elgin/Franklin field. As was discovered later, a gas leak had formed at the cover of well G4, which had been installed a few months earlier. A sequence and combination of several individual events never seen before had led to a kind of stress corrosion, which occurred only on G4. The incident was caused mainly by a chalk layer about 1000 m above the gas reservoir.



Figure 2. The Elgin Wellhead drilling platform is one of more than 400 rigs located in the North Sea.


The Elgin Wellhead drilling platform is one of more than 400 rigs located in the North Sea.


Charlie Chong/ Fion Zhang http://www.theoildrum.com/node/9072


As a consequence, a severe methane gas leak developed in this area. Production was halted, and the drilling platform crew was evacuated, because the exact position of the leak and the amount of gas emitted could not be determined. Additionally, it was not known whether the flame on top of the platform was still burning. Because of the danger of a possible explosion, a three-mile no-go area surrounding the rig was declared, and another 4000-ft exclusion zone was established in the airspace above the rig.

However, these precautions complicated the initial efforts to close the leak, as appropriate countermeasures could be attempted only after the gas concentration at the accident location had fallen below a critical value. Since these exposure limits did not permit taking a direct gas probe and subsequent gas analysis, an alternative method had to be considered to determine the methane content in the environment from afar. It was found in an absorption measurement of the infrared light in hydrocarbons.



IR absorption of hydrocarbons Hydrocarbons are chemical compounds that consist only of carbon and

hydrogen. Their simplest configuration is methane, a colorless and odorless combustible gas having the notation CH4. Its molecular model is shown in Figure 1.2 Its four C-H bonds are pointing toward the corners of a tetrahedron.This molecule structure exhibits four atomic oscillation modes, differentiated by either generating a temporal dipole moment – modes (a) and (d) – or not – modes (b) and (c). Only the first two can be excited by an external infrared radiation. They have a transmission spectrum shown in Figure 1 for the wave number area reaching from 4000/cm (which relates to a wavelength of 2.5 µm) to 500/cm (20 µm).

A wave number of 3019/cm (3.3-µm wavelength) relates to the absorption band of the antisymmetrical valence oscillation (a), whereas the deformation oscillation (d), whose movement is similar to the unfolding of an umbrella, causes a strong attenuation around a wavelength of 7.6 µm (at a wave number of 1306/cm). Both areas are suited for remote methane gas sniffing, with the stronger attenuation value favoring the use of the MWIR band around 3.3 µm. Additionally, it would be advantageous if the image components in the visible spectrum were captured as well for a spatial assignment.



MWIR camera with extended spectrum area In the case of the gas leak at the Elgin Wellhead drilling platform, the measurement task was defined primarily as visualizing the gas components (methane, butane and carbon dioxide), as well as the characteristics of their spreading in the form of a gas cloud close to the sea surface and in the atmosphere. An additional goal was determining the activity of the flame on the platform. These investigations were carried out by TIB Infrared Solutions, in cooperation with the laboratory for environmental measurements at the University of Applied Sciences Düsseldorf.

The Onca MWIR camera from Xenics, with expanded spectral coverage, was used for this purpose (Figure-3).

The Onca camera family is equipped with a Stirling-cooled detector array in mercury-cadmium-telluride (MCT) or InSb (why or ?) detector technology. It is especially well suited for research and development tasks with high-speed image capture or IR spectroscopy. The camera operates in the extended MWIR area from 3.7 to 4.8 µm, which can be further expanded to cover the 1 µm - to 5 µm wavelength area. This camera layout increases its all-weather and night-vision suitability and is of specific interest for spectroscopy applications.



Figure 3. The extended spectral area of an MWIR camera simplifies the spatial assignment of gas plumes to visible objects.



Using the TrueThermal technique, this camera system offers an accuracy of ±2 °C (or ±2 percent, whichever is largest). This is made possible by a new, stable method called NUC (nonuniformity correction), which eliminates the need for frequent adjustments. Four optional radiometric temperature ranges – −20 to 120 °C, 50 to 400 °C, 300 to 1200 °C and 1000 to 2000 °C – cover a wide variety of applications.

The camera platform is optimized for autonomous operation and also in combination with a PC. Among other valuable features, it offers a mode for real-time image correction. The area-array sensor is available with a standard resolution of 320 × 256 pixels (InSb) or 384 × 288 pixels (MCT), or in a high-resolution version featuring 640 × 512 pixels. Both versions offer the sensitivity specification NETD (noise-equivalent temperature difference) of less than 20 mK (?) .



The camera output delivers image The camera output delivers image data that is 14 bits wide at various frame rates. Two speeds are available: 30-Hz standard video with 640 × 512 pixels, and 60-Hz with 320 × 256 (InSb) or 384 × 288 (MCT) pixels. Additionally, 100 Hz is available at high resolution, as well as an extremely fast version with 460 Hz and 320 × 256-pixel resolution. Reading out partial images will further increase the frame rate, which is especially useful for process-control applications at high frame rates. The camera functions can be tailored to the specific application, with the parameters stored in the camera’s nonvolatile memory.

To adapt the camera to a specific measurement procedure, five filter-position options have been incorporated. Unlike most filter holders, which accept just one 25-mm filter of 1-mm thickness, the holders on the Onca’s filter wheel are much deeper, and each position can hold several filters up to a total thickness of 3 mm for spectral measurements.

The camera is user-programmable to offer individual filter positions and integration times for each exposure. However, because of the additional time needed for changing the filter and readjusting the operational parameters, the maximum frame rate mentioned above cannot always be reached.



This flexibility, together with a stable thermal calibration across various integration times, enables a new operational mode called SuperFraming, which delivers thermal images of a high dynamic range in real time derived from images specifically exposed to users’ specifications. Using this special operational mode, the user can locate hot and cold spots in an image for fast process-monitoring sequences.

Camera control and image capture are laid out for more than 100 images per second. Compatibility with GigE Vision and Camera Link simplifies the integration in user systems. For application development support, an API is available, as well as sample codes in C++, Visual Basic and Delphi; LabViewdrivers; and a comprehensive DLL library.



Remote gas measurement The solution to the complex measurement task of visualizing gas components leaking from the well close to the drilling platform and spreading as a plume over the sea surface into the atmosphere was deploying the high-resolution (640 × 512 pixels) MWIR camera with an extended wavelength area from 1to 5 µm, operating at a frame rate of 100 Hz. Using this type of camera broke new ground for the researchers. The exclusion zone forced the IRinvestigation to be done from a large distance. This was an operational condition, for which there were no previously established procedures or proven results.

The methane clouds can be detected even under these difficult measurement conditions; this is shown in an image taken from a plane flying over the scene (Figure 4). In the upper right is the drilling platform, with flame burning. The shadows visible in the foreground and in the center are caused by the methane gas plumes. They are illuminated by light reflections on the sea surface, and they absorb the midrange IR radiation at around 3.3 µm.



This image-capture process requires two filters, one for the bandpass around 3.3 µm, for methane absorption, and a second in the short-wave IR to make physical objects such as the drilling platform visible. By analyzing this dual-band image, certain gas concentrations can be assigned to fixed objects. This makes the interpretation of such images much easier. To detect gases whose transmission spectrum is different from that of methane, other filters or filter combinations are available. The results can be presented in different colors to distinguish among several gases in one image.

Taking aerial pictures of the gas-leak scene was not the only investigative method for determining the scope of the disturbance at the drilling platform. Examinations were also carried out from aboard a ship (Figure 5). They proved that the water molecules and drops suspended in the atmosphere above the sea level are causing a strong attenuation of the MWIR radiation. Despite this effect, the gas components located behind this water vapor can be determined because naturally occurring clouds appear fully saturated, whereas the gas plume appears more like a fog. Deploying the MWIR camera allowed a quick check of the working conditions so that a repair crew could be sent to the site. On May 15, the leak was plugged by discharging heavy mud into the well. After final closure with five cement plugs in October 2012, the drilling platform went back to operation in March 2013.



Figure 4. From above, methane plumes look like dark clouds in the MWIR spectrum.



Figure 5. The high-resolution, high-sensitivity MWIR camera Onca performs a checkup from sea level.



Figure 6. False-color representation of MWIR images enables the detection of the gas plume behind clouds formed by water vapor.



False-color representation of MWIR images enables the detection of the gas plume behind clouds formed by water vapor.



Gas leaking from a drilling platform

http://www.dailymail.co.uk/sciencetech/article-2125471/Total-gas-leak-Greenpeace-release-infra-red-image-explosive-gas-spewing-Elgin-rig.html#v-1535918156001



FLIR GF-Series Infrared Cameras for Safe Gas DetectionRefineries require state of the art technology to achieve results that are safe for the environment and safe for business. In fact our GF-Series infrared cameras have been developed together with oil industries and the American Petroleum Institute (API) to meet their requirements for detecting and minimizing gas leaks. The use of infrared cameras has already become a standard practice inmany oil and gas companies. It's a proactive way to identify sources of Volatile Organic Compound (VOC) emissions and repair leaking components before it's too late. By using the most advanced VOC detection, you will improve safety and productivity and minimize emissions.

■ http://www.flir.co.uk/ogi/display/?id=49559


Reading 3What is Emissivity

http://www.optotherm.com/emiss-physics.htm


More Reading: What is EmissivityAll objects and materials do not radiate infrared (thermal) energy equally. Emissivity is a term describing the efficiency with which a material radiates infrared energy. A blackbody has an emissivity of 1.00 and no other material can radiate more thermal energy at a given temperature. An object with an emissivity of 0 emits no infrared energy. Real-world objects have emissivity values between 0 and 1.00.


The lower emissivity of most real-world materials reduces the intensity of radiation from the theoretical predictions of Planck’s Law. The temperature of an object and its emissivity define how much infrared energy an object will emit. The figure below shows that quartz emits less energy than a blackbody at the same temperature and therefore has an emissivity below 1.00.


Physics of Infrared’s EmissivityInfrared (thermal) energy, when incident upon matter, be it solid, liquid or gas, will exhibit the properties of absorption σ, reflection ρ, and transmission τ to varying degrees.

Absorption σAbsorption is the degree to which infrared energy is absorbed by a material. Materials such as plastic, ceramic, and textiles are good absorbers. Thermal energy absorbed by real-world objects is generally retransferred to their surroundings by conduction, convection, or radiation.

Transmission τTransmission is the degree to which thermal energy passes through a material. There are few materials that transmit energy efficiently in the infrared region between 7µm and 14µm. Germanium is one of the few good transmitters of infrared energy and thus it is used frequently as lens material in thermal imaging systems.

Reflection ρReflection is the degree to which infrared energy reflects off a material. Polished metals such as aluminum, gold and nickel are very good reflectors. Conservation of energy implies that the amount of incident energy is equal to the sum of the absorbed, reflected, and transmitted energy.

(1) Incident Energy = Absorbed Energy Wσ + Transmitted Energy Wτ + Reflected Energy Wρ


τ


Emitted Energy = Absorbed Energy Consider equation 1 for an object in a vacuum at a constant temperature. Because it is in a vacuum, there are no other sources of energy input to the object or output from the object. The absorbed energy by the object increases its thermal energy - the transmitted and reflected energy does not. In order for the temperature of the object to remain constant, the object must radiate the same amount of energy as it absorbs. (2) Emitted Energy = Absorbed Energy

Therefore, objects that are good absorbers are good emitters and objects that are poor absorbers are poor emitters. Applying equation 2, Equation 1 can be restated as follows: (3) Incident Energy = Emitted Energy + Transmitted Energy + Reflected Energy

Setting the incident energy equal to 100%, the equation 3 becomes: (4) 100% = %Emitted Energy + %Transmitted Energy + %Reflected Energy

Because emissivity equals the efficiency with which a material radiates energy, equation 4 can be restated as follows: (5) 100% = Emissivity + %Transmitted Energy + %Reflected Energy

Applying similar terms to %Transmitted Energy and %Reflected Energy, (6) 100% = Emissivity + Transmissivity + Reflectivity



According to equation 6, there is a balance between emissivity, transmissivity, and reflectivity. Increasing the value of one of these parameters requires a decrease in the sum of the other two parameters. If the emissivity of an object increases, the sum of its transmissivity and reflectivity must decrease. Likewise, if the reflectivity of an object increases, the sum of its emissivity and trasmissivity must decrease.

Most solid objects exhibit very low transmission of infrared energy - the majority of incident energy is either absorbed or reflected. By setting transmissivity equal to zero, equation 6 can be restated as follows:

(7) 100% = Emissivity + Reflectivity

For objects that do not transmit energy, there is a simple balance between emissivity and reflectivity. If emissivity increases, reflectivity must decrease. If reflectivity increases, emissivity must decrease. For example, a plastic material with emissivity = 0.92 has reflectivity = 0.08. A polished aluminum surface with emissivity = 0.12 has reflectivity = 0.88.

The emissive and reflective behavior of most materials is similar in the visible and infrared regions of the electromagnetic spectrum. Polished metals, for example, have low emissivity and high reflectivity in both the visible and infrared. It is important to understand, however, that some materials that are good absorbers, transmitters, or reflectors in the visible, may exhibit completely different characteristics in the infrared.



Infrared Thermometer Emissivity tableshttp://www.scigiene.com/pdfs/428_InfraredThermometerEmissivitytablesrev.pdf


Infrared Thermometer Emissivity tables Understanding an object's emissivity or its characteristic "radiance" is a critical component in the proper handling of infrared measurements. Concisely, emissivity is the ratio of radiation emitted by a surface or blackbody and its theoretical radiation predicted from Planck's law. [W(L,T)=C1/(L^5*(exp(C2/LT)-1)] A material's surface emissivity is measured by the amount of energy emitted when the surface is directly observed. There are many variables that affect a specific object's emissivity, such as the wavelength of interest, field of view, the geometric shape of the blackbody, and temperature. However, for the purposes and applications of the infrared thermometer user, a comprehensive table showing the emissivity at corresponding temperatures of various surfaces and objects is displayed. The table below can be used to adjust the emissivity of any of the listed I.R. thermometers:

• TN408LC • TN418LD • TN40ALC • TN425LE

All have variable emissivity in order to improve the accuracy of the readings. For further assistance please contact us at Scigiene Corp. www.scigiene.com 416-261-4865 and we will be happy to assist. Non-Metal Emssivity table Material(Non-Metals) Temp degF(degC) Emissivity Adobe 68 (20) 0.9 Asbestos Board 100 (38) 0.96 Cement 32-392 (0-200) 0.96 Cement, Red 2500 (1371) 0.67 Cement, White 2500 (1371) 0.65 Cloth 199 (93) 0.9 Paper 100-700 (38-371) 0.93 Slate 68 (20) 0.97 Asphalt, pavement 100 (38) 0.93 Asphalt, tar paper 68 (20) 0.93 Basalt 68 (20) 0.72 Brick Red, rough 70 (21) 0.93 Gault Cream 2500-5000 (1371-2760) .26-.30 Fire Clay 2500 (1371) 0.75 Light Buff 1000 (538) 0.8 Lime Clay 2500 (1371) 0.43 Fire Brick 1832 (1000) .75-.80 Magnesite, Refractory 1832 (1000) 0.38 Grey Brick 2012 (1100) 0.75 Silica, Glazed 2000 (1093) 0.88 Silica, Unglazed 2000 (1093) 0.8 Sandlime 2500-5000 (1371-2760) .59-.63 Carborundum 1850 (1010) 0.92

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Material(Non-Metals) Temp degF(degC) Emissivity Ceramic Alumina on Inconel 800-2000 (427-1093) .69-.45 Earthenware, Glazed 70 (21) 0.9 Earthenware, Matte 70 (21) 0.93 Greens No. 5210-2C 200-750 (93-399) .89-.82 Coating No. C20A 200-750 (93-399) .73-.67 Porcelain 72 (22) 0.92 White Al2O3 200 (93) 0.9 Zirconia on Inconel 800-2000 (427-1093) .62-.45 Clay 68 (20) 0.39 Fired 158 (70) 0.91 Shale 68 (20) 0.69 Tiles, Light Red 2500-5000 (1371-2760) .32-.34 Tiles, Red 2500-5000 (1371-2760) .40-.51 Tiles,Dark Purple 2500-5000 (1371-2760) 0.78 Concrete Rough 32-2000 (0-1093) 0.94 Tiles, Natural 2500-5000 (1371-2760) .63-.62 Brown 2500-5000 (1371-2760) .87-.83 Black 2500-5000 (1371-2760) .94-.91 Cotton Cloth 68 (20) 0.77 Dolomite Lime 68 (20) 0.41 Emery Corundum 176 (80) 0.86 Glass Convex D 212 (100) 0.8 Convex D 600 (316) 0.8 Convex D 932 (500) 0.76 Nonex 212 (100) 0.82 Nonex 600 (316) 0.82 Nonex 932 (500) 0.78 Smooth 32-200(0-93) .92-.94 Granite 70 (21) 0.45 Gravel 100 (38) 0.28 Gypsum 68 (20) .80-.90 Ice, Smooth 32 (0) 0.97 Ice, Rough 32 (0) 0.98 Lacquer Black 200 (93) 0.96 Blue, on Al Foil 100 (38) 0.78 Clear, on Al Foil (2 coats) 200 (93) .08-.09 Clear, on Bright Cu 200 (93) 0.66 Clear, on Tarnished Cu 200 (93) 0.64 Red, on Al Foil (2 coats) 100 (38) .60-.74 White 200 (93) 0.95 White, on Al Foil (2 coats) 100 (38) .69-.88 Yellow, on Al Foil (2 coats) 100 (38) .57-.79 Lime Mortar 100-500 (38-260) .90-.92

Material(Non-Metals) Temp degF(degC) Emissivity Lacquer - continued Limestone 100 (38) 0.95 Marble, White 100 (38) 0.95 Smooth, White 100 (38) 0.56 Polished Grey 100 (38) 0.75 Mica 100 (38) 0.75 Oil on Nickel 0.001 Film 72 (22) 0.27 0.002 " 72 (22) 0.46 0.005 " 72 (22) 0.72 Thick " 72 (22) 0.82 Oil, Linseed On Al Foil, uncoated 250 (121) 0.09 On Al Foil, 1 coat 250 (121) 0.56 On Al Foil, 2 coats 250 (121) 0.51 On Polished Iron, .001 Film 100 (38) 0.22 On Polished Iron, .002 Film 100 (38) 0.45 On Polished Iron, .004 Film 100 (38) 0.65 On Polished Iron, Thick Film 100 (38) 0.83 Paints Blue, Cu2O3 75 (24) 0.94 Black, CuO 75 (24) 0.96 Green, Cu2O3 75 (24) 0.92 Red, Fe2O3 75 (24) 0.91 White, Al2O3 75 (24) 0.94 White, Y2O3 75 (24) 0.9 White, ZnO 75 (24) 0.95 White, MgCO3 75 (24) 0.91 White, ZrO2 75 (24) 0.95 White, ThO2 75 (24) 0.9 White, MgO 75 (24) 0.91 White, PbCO3 75 (24) 0.93 Yellow, PbO 75 (24) 0.9 Yellow, PbCrO4 75 (24) 0.93 Paints, Aluminium 100 (38) .27-.67 10% Al 100 (38) 0.52 26% Al 100 (38) 0.3 Dow XP-310 200 (93) 0.22 Paints, Bronze Low .34-.80 Gum Varnish (2 coats) 70 (21) 0.53 Gum Varnish (3 coats) 70 (21) 0.5 Cellulose Binder (2 coats) 70 (21) 0.34 Paints, Oil All colours 200 (93) .92-.96 Black 200 (93) 0.92 Black Gloss 70 (21) 0.9 Camouflage Green 125 (52) 0.85

Material(Non-Metals) Temp degF(degC) Emissivity Paints, Oil - continued Flat Black 80 (27) 0.88 Flat White 80 (27) 0.91 Grey-Green 70 (21) 0.95 Green 200 (93) 0.95 Lamp Black 209 (98) 0.96 Red 200 (93) 0.95 White 200 (93) 0.94 Quartz, Rough, Fused 70 (21) 0.93 Glass, 1.98 mm 540 (282) 0.9 Glass, 1.98 mm 1540 (838) 0.41 Glass, 6.88 mm 540 (282) 0.93 Glass, 6.88 mm 1540 (838) 0.47 Opaque 570 (299) 0.92 Opaque 1540 (838) 0.68 Red Lead 212 (100) 0.93 Rubber, Hard 74 (23) 0.94 Rubber, Soft, Grey 76 (24) 0.86 Sand 68 (20) 0.76 Sandstone 100 (38) 0.67 Sandstone, Red 100 (38) .60-.83 Sawdust 68 (20) 0.75 Shale 68 (20) 0.69 Silica,Glazed 1832 (1000) 0.85 Silica, Unglazed 2012 (1100) 0.75 Silicon Carbide 300-1200 (149-649) .83-.96 Silk Cloth 68 (20) 0.78 Slate 100 (38) .67-.80 Snow, Fine Particles 20 (-7) 0.82 Snow, Granular 18 (-8) 0.89 Soil Surface 100 (38) 0.38 Black Loam 68 (20) 0.66 Plowed Field 68 (20) 0.38 Soot Acetylene 75 (24) 0.97 Camphor 75 (24) 0.94 Candle 250 (121) 0.95 Coal 68 (20) 0.95 Stonework 100 (38) 0.93 Water 100 (38) 0.67 Waterglass 68 (20) 0.96 Wood Low .80-.90 Beech Planed 158 (70) 0.94 Oak, Planed 100 (38) 0.91 Spruce, Sanded 100 (38) 0.89

Metal Emssivity table Material(metal) Temp degF (degC) Emissivity Alloys 20-Ni, 24-CR, 55-FE, Oxid. 392 (200) 0.9 20-Ni, 24-CR, 55-FE, Oxid. 932(500) 0.97 60-Ni, 12-CR, 28-FE, Oxid. 518 (270) 0.89 60-Ni, 12-CR, 28-FE, Oxid. 1040 (560) 0.82 80-Ni, 20-CR, Oxidised 212 (100) 0.87 80-Ni, 20-CR, Oxidised 1112 (600) 0.87 80-Ni, 20-CR, Oxidised 2372 (1300) 0.89 Aluminium Unoxidised 77 (25) 0.02 Unoxidised 212 (100) 0.03 Unoxidised 932 (500) 0.06 Oxidised 390 (199) 0.11 Oxidised 1110 (599) 0.19 Oxidised at 599degC(1110degF) 390 (199) 0.11 Oxidised at 599degC(1110degF) 1110 (599) 0.19 Heavily Oxidised 200 (93) 0.2 Heavily Oxidised 940 (504) 0.31 Highly Polished 212 (100) 0.09 Roughly Polished 212 (100) 0.18 Commercial Sheet 212 (100) 0.09 Highly Polished Plate 440 (227) 0.04 Highly Polished Plate 1070 (577) 0.06 Bright Rolled Plate 338 (170) 0.04 Bright Rolled Plate 932 (500) 0.05 Alloy A3003, Oxidised 600 (316) 0.4 Alloy A3003, Oxidised 900 (482) 0.4 Alloy 1100-0 200-800 (93-427) 0.05 Alloy 24ST 75 (24) 0.09 Alloy 24ST, Polished 75 (24) 0.09 Alloy 75ST 75 (24) 0.11 Alloy 75ST, Polished 75 (24) 0.08 Bismuth, Bright 176 (80) 0.34 Bismuth, Unoxidised 77 (25) 0.05 Bismuth, Unoxidised 212 (100) 0.06 Brass 73% Cu, 27% Zn, Polished 476 (247) 0.03 73% Cu, 27% Zn, Polished 674 (357) 0.03 62% Cu, 37% Zn, Polished 494 (257) 0.03 62% Cu, 37% Zn, Polished 710 (377) 0.04 83% Cu, 17% Zn, Polished 530 (277) 0.03 Matte 68 (20) 0.07 Burnished to Brown Colour 68 (20) 0.4 Cu-Zn, Brass Oxidised 392 (200) 0.61 Cu-Zn, Brass Oxidised 752 (400) 0.6 Cu-Zn, Brass Oxidised 1112 (600) 0.61

Material(metal) Temp degF (degC) Emissivity Brass - continued Unoxidised 77 (25) 0.04 Unoxidised 212 (100) 0.04 Cadmium 77 (25) 0.02 Carbon Lampblack 77 (25) 0.95 Unoxidised 77 (25) 0.81 Unoxidised 212 (100) 0.81 Unoxidised 932 (500) 0.79 Candle Soot 250 (121) 0.95 Filament 500 (260) 0.95 Graphitized 212 (100) 0.76 Graphitized 572 (300) 0.75 Graphitized 932 (500) 0.71 Chromium 100 (38) 0.08 Chromium 1000 (538) 0.26 Chromium, Polished 302 (150) 0.06 Cobalt, Unoxidised 932 (500) 0.13 Cobalt, Unoxidised 1832 (1000) 0.23 Columbium, Unoxidised 1500 (816) 0.19 Columbium, Unoxidised 2000 (1093) 0.24 Copper Cuprous Oxide 100 (38) 0.87 Cuprous Oxide 500 (260) 0.83 Cuprous Oxide 1000 (538) 0.77 Black, Oxidised 100 (38) 0.78 Etched 100 (38) 0.09 Matte 100 (38) 0.22 Roughly Polished 100 (38) 0.07 Polished 100 (38) 0.03 Highly Polished 100 (38) 0.02 Rolled 100 (38) 0.64 Rough 100 (38) 0.74 Molten 1000 (538) 0.15 Molten 1970 (1077) 0.16 Molten 2230 (1221) 0.13 Nickel Plated 100-500 (38-260) 0.37 Dow Metal 0.4-600 (-18-316) 0.15 Gold Enamel 212 (100) 0.37 Plate (.0001) ·· ·· Plate on .0005 Silver 200-750 (93-399) .11-.14 Plate on .0005 Nickel 200-750 (93-399) .07-.09 Polished 100-500 (38-260) 0.02 Polished 1000-2000 (538-1093) 0.03 Haynes Alloy C, Oxidised 600-2000 (316-1093) .90-.96

Material(metal) Temp degF (degC) Emissivity Haynes Alloy 25, Oxidised 600-2000 (316-1093) .86-.89 Haynes Alloy X, Oxidised 600-2000 (316-1093) .85-.88 Inconel Sheet 1000 (538) 0.28 Inconel Sheet 1200 (649) 0.42 Inconel Sheet 1400 (760) 0.58 Inconel X, Polished 75 (24) 0.19 Inconel B, Polished 75 (24) 0.21 Iron Oxidised 212 (100) 0.74 Oxidised 930 (499) 0.84 Oxidised 2190 (1199) 0.89 Unoxidised 212 (100) 0.05 Red Rust 77 (25) 0.7 Rusted 77 (25) 0.65 Liquid 2760-3220 (1516-1771) .42-.45 Cast Iron Oxidised 390 (199) 0.64 Oxidised 1110 (599) 0.78 Unoxidised 212 (100) 0.21 Strong Oxidation 40 (104) 0.95 Strong Oxidation 482 (250) 0.95 Liquid 2795 (1535) 0.29 Wrought Iron Dull 77 (25) 0.94 Dull 660 (349) 0.94 Smooth 100 (38) 0.35 Polished 100 (38) 0.28 Lead Polished 100-500 (38-260) .06-.08 Rough 100 (38) 0.43 Oxidised 100 (38) 0.43 Oxidised at 1100 100 (38) 0.63 Gray Oxidised 100 (38) 0.28 Magnesium 100-500 (38-260) .07-.13 Magnesium Oxide 1880-3140 (1027-1727) .16-.20 Mercury 32 (0) 0.09 Mercury 77 (25) 0.1 Mercury 100 (38) 0.1 Mercury 212 (100) 0.12 Molybdenum 100 (38) 0.06 Molybdenum 500 (260) 0.08 Molybdenum 1000 (538) 0.11 Molybdenum 2000 (1093) 0.18 Molybdenum Oxidised at 1000degF 600 (316) 0.8 Molybdenum Oxidised at 1000degF 700 (371) 0.84

Material(metal) Temp degF (degC) Emissivity Lead - continued Molybdenum Oxidised at 1000degF 800 (427) 0.84 Molybdenum Oxidised at 1000degF 900 (482) 0.83 Molybdenum Oxidised at 1000degF 1000 (538) 0.82 Monel, Ni-Cu 392 (200) 0.41 Monel, Ni-Cu 752 (400) 0.44 Monel, Ni-Cu 1112 (600) 0.46 Monel, Ni-Cu Oxidised 68 (20) 0.43 Monel, Ni-Cu Oxid. at 1110degF 1110 (599) 0.46 Nickel Polished 100 (38) 0.05 Oxidised 100-500 (38-260) .31-.46 Unoxidised 77 (25) 0.05 Unoxidised 212 (100) 0.06 Unoxidised 932 (500) 0.12 Unoxidised 1832 (1000) 0.19 Electrolytic 100 (38) 0.04 Electrolytic 500 (260) 0.06 Electrolytic 1000 (538) 0.1 Electrolytic 2000 (1093) 0.16 Nickel Oxide 1000-2000 (538-1093) .59-.86 Palladium Plate (.00005 on .0005 silver) 200-750 (93-399) .16-.17 Platinum 100 (38) 0.05 Platinum 500 (260) 0.05 Platinum 1000 (538) 0.1 Platinum, Black 100 (38) 0.93 Platinum, Black 500 (260) 0.96 Platinum, Black 2000 (1093) 0.97 Platinum Oxidised at 1100 500 (260) 0.07 Platinum Oxidised at 1100 1000 (538) 0.11 Rhodium Flash (0.0002 on 0.0005 Ni) 200-700 (93-371) .10-.18 Silver Plate (0.0005 on Ni) 200-700 (93-371) .06-.07 Polished 100 (38) 0.01 Polished 500 (260) 0.02 Polished 1000 (538) 0.03 Polished 2000 (1093) 0.03 Steel Cold Rolled 200 (93) .75-.85 Ground Sheet 1720-2010 (938-1099) .55-.61 Polished Sheet 100 (38) 0.07 Polished Sheet 500 (260) 0.1 Polished Sheet 1000 (538) 0.14 Mild Steel, Polished 75 (24) 0.1 Mild Steel, Smooth 75 (24) 0.12 Mild Steel,liquid 2910-3270 (1599-1793) 0.28 Steel, Unoxidised 212 (100) 0.08

Material(metal) Temp degF (degC) Emissivity Steel - continued Steel, Oxidised 77 (25) 0.8 Steel Alloys Type 301, Polished 75 (24) 0.27 Type 301, Polished 450 (232) 0.57 Type 301, Polished 1740 (949) 0.55 Type 303, Oxidised 600-2000 (316-1093) .74-.87 Type 310, Rolled 1500-2100 (816-1149) .56-.81 Type 316, Polished 75 (24) 0.28 Type 316, Polished 450 (232) 0.57 Type 316, Polished 1740 (949) 0.66 Type 321 200-800 (93-427) .27-.32 Type 321 Polished 300-1500 (149-815) .18-.49 Type 321 w/BK Oxide 200-800 (93-427) .66-.76 Type 347, Oxidised 600-2000 (316-1093) .87-.91 Type 350 200-800 (93-427) .18-.27 Type 350 Polished 300-1800 (149-982) .11-.35 Type 446, Polished 300-1500 (149-815) .15-.37 Type 17-7 PH 200-600 (93-316) .44-.51 Type 17-7 PH Polished 300-1500 (149-815) .09-.16 Type C1020,Oxidised 600-2000 (316-1093) .87-.91 Type PH-15-7 MO 300-1200 (149-649) .07-.19 Stellite, Polished 68 (20) 0.18 Tantalum, Unoxidised 1340 (727) 0.14 Tantalum, Unoxidised 2000 (1093) 0.19 Tantalum, Unoxidised 3600 (1982) 0.26 Tantalum, Unoxidised 5306 (2930) 0.3 Tin, Unoxidised 77 (25) 0.04 Tin, Unoxidised 212 (100) 0.05 Tinned Iron, Bright 76 (24) 0.05 Tinned Iron, Bright 212 (100) 0.08 Titanium Alloy C110M,Polished 300-1200 (149-649) .08-.19 Oxidised at 538degC(1000degF) 200-800 (93-427) .51-.61 Alloy Ti-95A,Oxidised at 538degC(1000degF) 200-800 (93-427) .35-.48 Anodized onto SS 200-600 (93-316) .96-.82 Tungsten Unoxidised 77 (25) 0.02 Unoxidised 212 (100) 0.03 Unoxidised 932 (500) 0.07 Unoxidised 1832 (1000) 0.15 Unoxidised 2732 (1500) 0.23 Unoxidised 3632 (2000) 0.28 Filament (Aged) 100 (38) 0.03 Filament (Aged) 1000 (538) 0.11 Filament (Aged) 5000 (2760) 0.35 Uranium Oxide 1880 (1027) 0.79

Material(metal) Temp degF (degC) Emissivity Zinc Bright, Galvanised 100 (38) 0.23

Commercial 99.1% 500 (260) 0.05 Galvanised 100 (38) 0.28

Oxidised 500-1000 (260-538) Polished 100 (38) 0.02 Polished 500 (260) 0.03 Polished 1000 (538) 0.04 Polished 2000 (1093) 0.06


Effects of EmissivityThermal imaging cameras detect and measure the sum of infrared energy over a range of wavelengths determined by the sensitivity of the camera’s detector. Thermal imagers cannot discriminate energy at 7µm from energy at 14µm the way the human eye can distinguish various wavelengths of light as colors. They calculate the temperature objects by detecting and quantifying the emitted energy over the operational wavelength range of the detector. Temperature is then calculated by relating the measured energy to the temperature of a blackbody radiating an equivalent amount of energy according to Planck’s Blackbody Law.

Because the emissivity of an object affects how much energy an object emits, emissivity also influences a thermal imager’s temperature calculation. Consider the case of two objects at the same temperature, one having high emissivity and the other low. Even though the two objects have the same temperature, the one with the low emissivity will radiate less energy. Consequently, the temperature calculated by the thermal imager will be lower than that calculated for the high emissivity object.

http://www.optotherm.com/emiss-physics.htmc


DiscussionSubject: They (Infrared Cameras) calculate the temperature of the objects by detecting and quantifying the emitted energy over the operational wavelength range of the detector. Temperature is then calculated by relating the measured energy to the temperature of a blackbody radiating an equivalent amount of energy according to Planck’s Black-body Law.



Apparent TemperatureThermal imaging cameras cannot detect the emissivity of objects in order to calculate their true temperature. They can only calculate the “apparent” temperature of objects. The apparent temperature of an object is a function of both its temperature and emissivity. Given two objects with the same true temperature but different emissivity, a higher apparent temperature will be calculated for the object with higher emissivity (see figure below). Given two objects with the same emissivity but different true temperature, a higher apparent temperature will be calculated for the object with higher true temperature. The apparent temperature of an object may be substantially different from its true temperature. Only when the emissivity of objects is known can thermal imagers compensate for emissivity and calculate true temperature.



ReflectivityObjects with high reflectivity can reflect energy radiated by other objects. For example, polished aluminum reflects about 90% of the energy incident upon its surface. Just as thermal imagers cannot detect the emissivity of objects in order to calculate their true temperature, they also can’t detect the reflectivity of objects. Therefore, when calculating the apparent temperature of an object, thermal imagers detect and quantify energy emitted from the object, as well as, energy reflected from the surface of the object. If an object reflects energy from another radiating source with a higher temperature, the apparent temperature that is calculated for the object will be higher than its true temperature. Likewise, if an object reflects energy from another radiating source with a lower temperature, the apparent temperature that is calculated for the object will be lower than its true temperature.

Given two objects with the same true temperature but different emissivity, a higher apparent temperature will be calculated for the object with higher emissivity (see figure below). Given two objects with the same emissivity but different true temperature, a higher apparent temperature will be calculated for the object with higher true temperature. The apparent temperature of an object may be substantially different from its true temperature. Only when the emissivity of objects is known can thermal imagers compensate for emissivity and calculate true temperature.



Emissivity Makes a Temperature Difference: Blackbody Calibrator

■ https://www.youtube.com/embed/JElKE-ADXr8

https://www.youtube.com/watch?v=JElKE-ADXr8


What are Emissivity and Reflectivity and How do They Affect Infrared Temperature Reading

■ https://www.youtube.com/embed/W5x7fNZTwXE

https://www.youtube.com/watch?v=W5x7fNZTwXE


Emissivity ExamplesA material’s emissivity can vary at different wavelengths (selective emitter). Most materials, however, have relatively uniform emissivity throughout the wavelength range in which thermal imagers operate (grey body). For example, the emissivity of most plastics, ceramics, and metals does not vary significantly throughout the wavelength range of 7 to 14µm. Different materials can have widely different emissivity values within the range of 0 to 1.00 (see table below). Many common materials including plastics, ceramics, water, and organic materials have high emissivity. Uncoated metals may have very low emissivity. Polished stainless steel, for example, has an emissivity of approximately 0.1 and therefore emits only one tenth the amount of energy of a blackbody at the same temperature.

Material Emissivity Human Skin 0.98 ; Water 0.95 Aluminum (Polished) 0.10 ; Aluminum (Anodized) 0.65 ; Plastic 0.93 ; Ceramic 0.94 Glass 0.87 ; Rubber 0.90 ; Cloth 0.95

Note: The emissivity date in the table above are approximate values. The emissivity of a particular material depends on its specific chemical makeup and surface characteristics. Smooth, shiny surfaces, for example, tend to have higher reflectivity and thus, low emissivity.



Methods of Increasing EmissivityThe surface characteristics of a material determine its emissivity. To increase a material’s emissivity, it is necessary to increase the emissivity of its surface. Following are several methods of altering a material's surface to increase its

emissivity. For a given material, one or more of these approaches may be effective. Choose the method that is easiest to apply/remove and that has minimum affect on the temperature of the material. Apply coatings, treatments, liquids, tapes, or powders as thin as possible to prevent altering the thermal behavior of the original material. Example are:

Apply a thin layer of tape Apply a thin layer of paint, lacquer, or other high emissivity coating Apply a thin coating of baby powder or foot powder Apply a thin layer of oil, water, or other high emissivity liquid Apply a surface treatment such as anodizing Roughen the surface (may require substantial roughening)



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Charlie Chong/ Fion Zhanghttps://www.yumpu.com/en/browse/user/charliechong

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