sound power - method

8/6/2019 Sound Power - Method

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Sound Power

The total acoustic power transmitted. Sound power is a fundamental property of a sound

source, that is, the amount of acoustic power radiated into the environment. The sound

power output of a source can be likened to the thermal output of a space heater. A heaterrated for 1000 W can be expected to produce a given quantity of heat, but the temperaturethat will be experienced is influenced by proximity and the environment.

Typical sound power measurements are made by averaging a statistically significantnumber of measuring points around the radiating device. The computation of sound power

is the sound intensity multiplied by the area. Sound power level is the measurement in

decibels.

Units:

W

Measurement of the sound power emissions of the Unit Under Test (UUT) in reverberant,

anechoic or free-field test environments.

Equipment:

Motors/Generators

Rotating Machinery Recreational Equipment

Air-Moving Devices

Lawn and Garden Equipment Any Sound Generating Equipment

Frequency Range of Interest:

Generally the 1/3 octave bands centered between 100 Hz and 10 kHz. May be extended toinclude energy in the 16 kHz octave band. Information on emissions in the 31.5 Hz and 63

Hz octave bands are increasingly in demand for many types of mechanical equipment,

although it may be difficult to obtain data at these frequencies in full compliance with test

standard requirements.

Units:

LW or PWL in watts or decibels relative to 1x10-12 watts. May be expressed as a single A-weighted level or in 1/3-octave bands.Approaches:
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Approach 1

Direct Method in Free Field Test Environment

Approach

This measurement is based on the proportional relationship between the mean squarepressure and the sound intensity in an anechoic environment.

The sound pressure levels created by the UUT are sampled at a number of positions on a

measurement surface that envelops the UUT. The sound pressure levels are averaged over

the measurement surface. A term that accounts for the surface area of the measurementsurface is added to the average sound pressure level in order to determine the sound powerlevel of the UUT.

The mathematical relationship is:

Lw = Lp + 10 * log (S)

Where:Lw = Sound Power of UUT (in dB re 1x10-12 watts)

Lp = Average sound pressure level on the measurement surface (in dB re 2x10-5 Pa)

S = surface area of the measurement surface (in m2)(Note: An additional term for normalization to standard atmospheric pressure and

temperature may be applied)

The measurement surface is typically spherical, hemispherical, or a rectangular

parallelepiped.

Advantages/Disadvantages to Approach

+Yields precision-grade data with standard deviation of reproducibility


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instrumentation, using an appropriate digitizer and software (see products below).

The virtual instrument solution has the additional advantage that its function can be

changed at will by applying new software. Microphone Multiplexer (optional)

System Block Diagram

NI products commonly used for this measurement:

Sound Power System

NI 455X DAQ

NI 5911 Instrument

PCI-445X DAQ

Sound and Vibration Toolset

LabVIEW

Real-Time Octave Analyzer Software for NI 455X
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Approach 2

Comparison Method in a Free Field Test Environment

Approach

The free field test environment is a highly absorptive, but not anechoic environment.

Because of this, the relationship between mean squared pressure and sound power is notstrictly proportional. Therefore, this measurement is based on the use of a calibrated

reference sound source (RSS) and a comparison of the sound pressure levels generated by

the RSS to the sound pressure levels generated by the UUT.

The sound pressure levels created by the UUT and the RSS are sampled at a number of

positions on a measurement surface that envelops the RSS and UUT. The sound powerlevel of the UUT is determined from the known sound power output of the RSS, the sound

pressure level created by the RSS in the test environment, and the sound pressure level

created by the UUT in the test environment.


Lw (UUT) = Lw (RSS) [Lp(RSS) Lp(UUT)]

Where:

Lw(UUT) Sound power of the UUT (in dB re 1 x 10---12 watts)Lw(RSS) Calibrated Sound power of RSS (in dB re 1 x 10---12 watts)

Lp(RSS) Sound pressure level generated by RSS (in dB re 2 x 10-5 Pa)

Lp(UUT) Sound pressure level generated by UUT (in dB re 2 x 10-5 Pa)


-Yields engineering-grade data with standard deviation of reproducibility


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Reference Sound Source, calibrated in accordance with ISO 6926

Microphone(s) with uniform frequency response over frequency range of interest.

Integrating, averaging sound level meter with A-weighting and/or 1/3 octave bandfiltering.

Microphone Multiplexer (optional)



Sound Power System

NI 455X DAQ

PCI-445X DAQ

NI 5911 Instrument

Real Time Octave Analyzer Software for NI 455X


LabVIEW
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Approach 3

Direct Method in Reverberation Chamber

Approach

This measurement is based on the relationship between the sound power level of the UUT,

and the sound pressure levels it generates in a reverberant sound field with a knownreverberation time.

The space/time averaged sound pressure level generated by the UUT is determined bysampling the sound pressure levels in thereverberation chamberat a number of fixed

positions or over a traversed path. The reverberation time in the chamber is measured. The

sound power level of the UUT is determined from the average sound pressure level and thereverberation time.


Lw(UUT) = Lp(UUT) - 10*log(T) + 10*log (V) + 10*log[1+(S/8V)]-14.0

Where:Lw = Sound power of UUT (in dB re 1x10-12 watts)

Lp= Sound pressure level generated by UUT (in dB re 1x10-5 Pa)

T = Reverberation time in secondsV = volume of the reverberation chamber (in m3)

S= surface areas ofreverberation chamber (in m2)

= wavelength at center frequency of one-third octave band

(Note: An additional term for normalization to standard atmospheric pressure and

temperature may also be applied)




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Approach 4

Comparison Method in Reverberation Chamber

Approach

This measurement is based on the use of a calibrated reference sound source (RSS), and a

comparison of the sound pressure levels generated by the RSS to the sound pressure levelsgenerated by the UUT.

The space/time averaged sound pressure level generated by the UUT and RSS aredetermined by sampling the sound pressure levels in the reverberation chamber at a number

of fixed positions or over a traversed path. The sound power level of the UUT is

determined from the known sound power output of the RSS, the sound pressure levelcreated by the RSS in the reverberation chamber, and the sound pressure level created by

the UUT in the reverberation chamber.


Lw (UUT) = Lw (RSS) [Lp(RSS) Lp(UUT)]

Where:

Lw(UUT) Sound power of the UUT (in dB re 1 x 10---12 watts)

Lw(RSS) Calibrated Sound power of RSS (in dB re 1 x 10---12 watts)Lp(RSS) Sound pressure level generated by RSS (in dB re 2 x 10-5 Pa)

Lp(UUT) Sound pressure level generated by UUT (in dB re 2 x 10-5 Pa)




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10/22

Approach 5

Method Using Sound Intensity

Approach

This measurement is based on the measurement of the average sound intensity at a number

of points on a measurement surface that envelops the UUT. The mathematical relationshipis:

Lw (UUT) = LI + 10*log S

Where:

Lw(UUT) Sound power of the UUT (in dB re 1 x 10---12 watts)Li Average sound intensity over the measurement surface (in dB re 1X10-12 watts/m2)

S = surface area of the measurement surface (in m2)


-Yields engineering-grade data

- Has more limited frequency range depending on sound intensity probe configuration and

can require multiple passes to cover entire frequency range+ Can be conducted in less expensive test facilities and, in some cases, in-situ

+ Can be useful in identifying specific noise sources within a piece of equipment

- Requires more extensive instrumentation- More difficult to learn to use intensity based measurements

- Not accepted by many international standard test codes as sound power measurement

method

Industry Standards

ISO 9614-1, ISO 9614-2

Equipment

Reference Sound Source, calibrated in accordance with ISO 6926

Microphone with uniform frequency response over frequency range of interest.

Integrating/averaging sound level meter with A-weighting and/or 1/3 octave bandfiltering

Level versus time analyzer with reverberation time analysis
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Sound Power System


NI 455X DAQ

PCI-445X DAQ

NI 5911 Instrument

LabVIEW

Real-Time Octave Analysis SoftwareAdditional References

Related NI Products:

Sound Power System


Helpful Web Sites:

Acoustic Test Chambers and Environments

Measurement of Sound Absorption

Information Contributed By: David A. Nelson, P.E., INCE Bd. Cert. Nelson Acoustical

Engineering, Inc. specializes in noise and vibration control, sound quality, laboratory

facilities and test control systems, and instruction related to plants, buildings, laboratories,

products, and machinery.
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1/N octave analysis

Frequency Spectrum

The representation of a signal in the frequency domain. The signal is broken into multipleperiodic signals, each with an amplitude and phase. The frequency spectrum is useful foridentifying repeating signals, of which asine wave is the simplest.

Types of Frequency Spectra

A wide range of terminology has been used to describe various types of frequency spectra.

Frequency spectra can be broken down into three main groups:

1. Frequency Spectrum. (also known as Instantaneous Spectrum, Fourier Spectrum,

FFT Spectrum, orComplex Spectrum)

Here, the spectrum is measured on one block of data and no averaging is performed. The

spectrum consists of a number of periodic components (one vector per frequency), which

are most often displayed as magnitude and phase information. Most instruments do notshow the phase part. Normally the magnitude is expressed in Volts orpower ( V2). When

the FFT is used the compute the Frequency Spectrum, the frequency components will have

a linear spacing. For example, a 1000 point time block will be transformed into 500frequency components which are equally spaced. If constant percentage bandwidth analysis

is used (such as for1/3 octave analysis), then the frequency components are spaced on a

logarithmic axis. Each filter has a bandwidth which is a given percentage (26% for 1/3octave) of the center frequency of the filter.

2. Averaged Complex Spectrum. (also known as Averaged Fourier Spectrum)

Since a complex spectrum consists of both a magnitude and phase, it is only meaningful to

performing averaging of these spectra forrepeatedsignals acquired under identical trigger

conditions. This results in the acquired waveform being positioned with the same delayrelative to the trigger. The averaging is done on the real and imaginary components

individually, so that the phase information is retained. This type of measurement picks out

periodic frequency components and is very useful in removing noise that is not correlatedto the repeated signal.

If complex averaging is performed on non-repeating signals, the result will convergetoward zero, since the phases of the individual frequency components will be randomly

distributed for each acquisition and spectrum calculation.

To see this in practice, rundemo1 using the LabVIEW Player. Set the Number of Averagesto 4000, the Weighting Mode to "Linear", and set the Trigger "On". This sets up the

instrument to perform synchronous averaging on the sine signal. Now switch the Averaging

Mode between "RMS Averaging" and "Vector Averaging". Notice how the vector
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averaging reduces the noise, without affecting the level of the sine wave. Now turn the

trigger off, while still using "Vector Averaging" and notice that the level of the sine wave

now jumps around, since it is no longer being synchronously averaged.

To see the effect of synchronous averaging on the time domain signal, run demo 2where

you can also find a sine wave buried in noise.

3. Power Spectrum. (also known as autospectrum, autopower spectrum, orSpectrum)

These terms refer to an average of the power of the individual frequency components over

a number of instantaneous spectra. When this averaging occurs, the magnitude of eachfrequency component is squared, and added to the previous sum for that frequency. Hence,

the phase information is discarded.

The averaging to compute a power spectrum does not reduce the unwanted noise in thesystem. However, it can be extremely useful in getting a reliable statistical estimate of the

level ofrandom signals being measured. For example, if you only display the

instantaneous spectrum ofwhite noise, the spectrum will be extremely jagged. But aftercomputing the power spectrum with adequate averaging, the shape of the spectrum will

converge on a flat spectrum. Power spectra can be shown in units of power, or the square

root of the averaged result can be taken to give a voltage value (which is theRMSvalue).

In addition, the power spectrum may be scaled in several different ways, depending on the

type of signal you are analyzing::Power Spectral Density (PSD) andEnergy Spectral

Density (ESD).

PSD is used when measuring continuous broadband noise, and normalizes the

power to an equivalent bandwidth of 1 Hz, irrespective of the actual bandwidth of

the filter being used. For example, if a signal is measured at -93 dB in a 10 Hzbandwidth, then the spectral density would be -103 dB (in a 1 Hz bandwidth). This

makes it possible to compare noise measurements made with different bandwidth

settings of the spectrum analyzer.

ESD is used to measure the energy oftransient signals. Since transients also arespread out over a broad frequency range, they must be normalized to 1 Hz (as with

noise). In addition, the duration of transients may vary significantly, so their

duration is also normalized to a standard equivalent duration of 1 second. This

makes it possible to compare the spectra of different transients.

Notes on Terminology:

The term "frequency response of a signal" is often loosely used, but incorrectly. Frequency

response refers to the transfer characteristic of a system, that is, the input/output

relationship. For example, the gain and phase response of a filter. Likewise, the term "the

spectrum of a filter" is often incorrectly used when what really is mean is the frequency
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response of the filter.

Example of Measurements of Frequency Spectra on Random Noise Signals

If you are making an RMS measurement on a randomnoise signal, the error of the

measurement will typically be dominated by the effective number of statistical averagesyou perform, and not as much on the actual "sine wave" (data sheet) accuracy of the

instrument. The random error (with 95% confidence which corresponds to 2 sigma

(standard deviations)) of a measurement on random noise signals is equal to

where B = Bandwidth of the measurement in Hz

and T = the averaging time in seconds.

For example, if you measure random noise with a bandwidth of 100 Hz over 1 second, theerror will be equal to

1/(2 x 10) = 0.05 or 5%.

This means the correct value will lie between 0.95 and 1.05, which is within approximately

0.5 dB.

This equation is solved interactively and graphically in this link.

Demo 3 illustrates how the averaging reduces the variation of the correct value of the

spectral componenets of random noise. When you run the demo, notice that as the number

of averages increases, the noise floor of the spectrum becomes smoother, as it converges tothe correct value as determined by the equation above.

If you are measuring a sine wave and there is significant random noise present, the noisewill bias the value of the sine wave measurement to be too high. In cases of this nature, it is

best to use a spectrum analysis technique where the sine wave component can be separated

from the random noise components. The longer the measurement, the more noise can be

removed, and the less the value of the sine wave will be affected by the noise. Longmeasurement times make very narrow spectrummeasurements possible. This is also

illustrated indemo 3 using the LabVIEW Player.

Units:

V vs Hz
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Spectrum analysis using filters whose bandwidth is a fractional ratio of the center

frequency of the filter. For example, a 1/3 octave filter centered at 1000 Hz would have a

bandwidth of 260 Hz (26% equals 1/3 octave). Bandwidth (relative to a normalized centerfrequency of 1) is computed as 2 (1/N)-1. The typical bandwidths used (primarily for

acoustical and vibration ananlysis) are 1/1 octave, 1/3, 1/12, and 1/24 octave.

Octave band filters do not have infinitely steep skirts. Therefore, an isolated tone may

produce a reading in adjacent octave bands. Also, a tone at the nominal boundary between

two bands produces an equal reading in both. (For example, a 60 dB tone at 707.1 Hzwould give readings of 57 dB each in the 500 Hz and 1000 Hz octave bands.) Note also that

filters designed according to ANSI S1.11 and IEC 1260 filters have different skirts. Bands

adjacent to a strong tone may have different numerical readings with the two types offilters. The actual filter band center frequencies are typically developed as a series of

powers of 21/3 times 1000 Hz, and therefore, may not correspond precisely to the nominal

band center frequencies.

1/N octave filters have a constant relative bandwidth, which means that the Q factor of the

filters are the same. In many respects, this is similar to many natural systems, which tend to

have a similar behavior and are best viewed on a logarithmic frequency axis. For example,the frequency response of a simple (first order) low-pass filter looks like a straight line

when plotted on a logarithmic frequency axis.

The following is a table of octave and third-octave filter center frequencies:

ISO Band Numbers Octave Band Center

Frequency

One-Third Octave Band Center

Frequencies

11, 12, 13 16 Hz 12.5 Hz, 16 Hz, 20 Hz14, 15, 16 31.5 Hz 25 Hz, 31 Hz, 40 Hz

17, 18, 19 63 Hz 50 Hz, 63 Hz, 80 Hz

20, 21, 22 125 Hz 100 Hz, 125 Hz, 160 Hz

23, 24, 25 250 Hz 200 Hz, 250 Hz, 315 Hz

26, 27, 28 500 Hz 400 Hz, 500 Hz, 630 Hz

29, 30, 31 1000 Hz 800 Hz, 1000 Hz, 1250 Hz

32, 33, 34 2000 Hz 1600 Hz, 2000 Hz, 2500 Hz

35, 36, 37 4000 Hz 3150 Hz, 4000 Hz, 5000 Hz

38, 39, 40 8000 Hz 6300 Hz, 8000 Hz, 10000 Hz

41, 42, 43 16000 Hz 12500 Hz, 16000 Hz, 20000 Hz

Units:

V or dB vs.1/Oct (Hz)
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Frequency Response

Overview

The gain and phase response of a circuit or other unit under test at all frequencies ofinterest. Although the formal definition of frequency response includes both the gain andphase, in common usage, the frequency response often only implies the magnitude (gain).

The frequency response is defined as the inverse Fourier Transform of the Impulse

Response of a system.

Measurement

Frequency response measurements require the excitation of the unit under test(UUT) with

energy at all relevant frequencies. The fastest way to perform the measurement is to use abroadband excitation signal that excites all frequencies simultaneous, and use FFT-based

techniques to measure at all of these frequencies at the same time. Noise and non-linearity

is best minimized by using random noise excitation, but short impulses or rapidsweeps

(chirps) may also be used.

When the desired resolution bandwidth of interest is less than about 100 kHz, the fastest

way to measure the frequency response functions is to use an FFT-based technique.

The bookRandom Data, Analysis and Measurement Procedures by Bendat and Pierson, is

considered a definitive work on the error estimation techniques for the various classes ofmeasurements (Second Edition/Third Edition) . The mathematical convetions and symbols

used by Bendat and Piersol are used in this glossary.

For proper measurement, it is also important to understand the nature of the type of signals

that you are dealing with. Please see Signal Types.

Units

dB V vs. Hz

rad (or degrees) vs. Hz

Measurement Approaches

Sine Generator/Voltmeter
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You apply a sine wave to the input of the system under test, and measure the output

voltage. Then, repeat this process for each frequency. The gain of the system is the ratio of

the output voltage to the input voltage.

Sine Generator/Phase Meter (for Phase Measurements)

Apply a sine wave to the input, and measure the phase of the output relative to the input at

each frequency of interest.

This method has the advantage of being low-cost and simple. It is also quite slow, and thefollowing assumptions must be fulfilled in order for the measurement to be accurate:

1. The output voltage of the signal generator is stable during the entire measurement,

and also at all frequencies. If there is doubt about this, the voltage must be measured

at each frequency.2. The system does not create significant distortion.

3. There is no significant noise on the output of the system. Otherwise, the measuredoutput voltage will be too high.

As a rule of thumb, if there is 1% distortion or noise in the system, the error will beof the same order of magnitude.

4. The output must be statistically correlated to the input. This assumption is normally

true in high fidelity analog systems. However, in mechanical systems, as well assystems with complex transmission mechanism (RF) and/or with digital encoding,

echo cancelling, and other adaptive techniques, this assumption may not be fulfilled.

To account for all of the above, you can use digital signal processing techniques, including

FFT and cross spectral methods.

Swept Sine Excitation

Use a swept sine wave generator and an associated voltmeter. You must set the averaging

time of the voltmeter so that it is less than the dwell time in a given frequency range.

This method requires for you to meet the following criteria:

1. The sweep time for a given bandwidth must be greater than the reciprocal of thedesired bandwidth. For example, if a 100-Hz resolution is desired, the sweep time

for the 100 Hz must be at least 10 ms.

2. The integration time of the voltmeter must be short enough to the 10 ms dwell time,

otherwise it cannot respond fully.

This is a variant of the first method in that it uses continuous swept sine waves, instead of

discretely stepped sine waves. This variation can be faster than the Sine Generator / Phase

Meter method described above, but it must fulfill the same assumptions.


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Certain instruments may have "adaptive sweep," where the sweep rate adapts to the rate of

change of the output signal. For example, when sweeping through a very sharp resonance,

the sweep rate is reduced to fully resolve the resonance peak.

Click on demo for an interactive demonstration using the LabVIEW Player.

Swept Sine with Tracking Filtering

Similar to the Swept Sine Excitation method described above, but this method has the

advantage of being able to reject noise and distortion from the system by using a filter onthe output that follows the frequency of the input.

This method must meet all the requirements regarding dwell time and averaging times.

A sophisticated variant of this method offsets (delays) the receiving filter with a fixed

frequency offset (corresponding to a fixed time delay), and makes it possible to measure the

frequency response of delayed signal paths. For example, in acoustic applications, you canmeasure the frequency response of the signal reflected from the ceiling.

Sensors

When making this measurement, you should make sure that the output impedanceof the

sine generator is low compared to the input impedance of the unit under test. Otherwise, theactual input voltage applied may drop, or be changed as a function of frequency.

Transient or Noise Excitation with Cross Spectral Techniques

You can use any signal that contains frequency components in the range of interest. Thesignals aren't required to have the same amplitude. However, all measurements using Cross

Spectral Techniques require simultaneous measurement of both input and output signals,

using simultaneously sampling A/D Converters.

The frequency response can be computed as

where is the cross spectrum and is the autospectrum of the input.

This technique computes the correlation between the input and output signal (as a function

of frequency) and hence, rejects noise and distortion. The more statistical samples that are

included in the averaging, the greater the noise and distortion rejection and hence, thegreater the accuracy of the measurement. The resulting statistical function, called the cross

spectrum, is then normalized for the actual amplitude of the signal at each frequency on the

input (called the autospectrum, or more commonly, the averaged spectrum). This gives the
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Frequency Response Function (FRF), which contains both magnitude and phase

information. The magnitude is typically shown on a logarithmic Y axis (in dB), and the

phase is often shown on a 0 to 360 degree scale. In systems with output noise, the mostaccurate evaluation of resonance peaks is made using the H2 method of frequency response

computation, whereas the H1 technique gives the best response for anti-resonances. H2 is

also useful when inadequate resolution is used in the measurement of a resonancel.

However, since the phase often shifts thousands of degrees, a technique calledphase

unwrappingis used, to remove the discontinuities every time the phase jumps from 360 to

0 degrees. A demo of frequency response with phase measurement can be seen by clicking

demo for use with the LabVIEW Player.

This approach has the advantage of overcoming noise, distortion, and non-correlated

effects. It also corrects for any loading effects on the input to the system. In addition, the

technique can be extremely rapid, because it measures all frequencies of interest

simultaneously. Its only weakness is that its signal-to-noise ratio can be lower than the

swept sine with tracking filter technique.

Click on demo for an interactive demonstration of frequency response (gain only, no phase)

using the LabVIEW Player.

Naturally Occurring Excitation

Sometimes you cannot insert an excitation signal into the system to be tested. However, if

you want to measure the Frequency Response Function of a shock absorber in a car, youcan use the naturally occurring "input signals" coming from bumps in the road as the

excitation signals. Using cross spectral techniques, you can measure the input signal on the

axle of the wheel and cross correlate it with the output signal picked up on the automotivechassis. Since the bumps are transients, they have relatively broad frequency componentsand make a broadband measurement possible.

When making this measurement, you should take extreme care to account for triggering and

windowing conditions, and also consider potential time delays between the input andoutput. Thus, this technique is only recommended for experienced professionals with a

thorough understanding of digital signal processing techniques.
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A weighting

A frequency-dependent weighting of sound signals, which has the greatest sensitivity in the

1 kHz to 5 kHz range -- corresponding to the range of the greatest sensitivity of the human

ear.A weightingis the most common frequency weighting used for sound-level meters. TheB and C weightings have similar responses to the mid-frequency range, but have greater

sensitivity at the lowerfrequencies. The B and C weightings were originally meant to

mimic the behavior of the ear at higher sound levels, but in practice, the A weighting hasbeen the most widely used network.

Anechoic Chamber

An enclosure especially designed with walls that absorb sound or radiation, creating an

essentially free-field environment for testing. Anechoic chambers are used both for acoustic

measurements and for RF measurements.

Acoustic anechoic chambers have surfaces that absorb more than 99% of incident sound

energy over the frequency range of interest, thereby approximating a free field. Room

surfaces are covered with sound-absorbing wedges. Anechoic chambers are used inprecision-grade measurements.

Sound Pressure Level

Sound pressure is the dynamic variation of the static pressure of air and is measured inforce per unit area. Sound pressure is normally represented on a logarithmic amplitude

scale, which gives a better relationship to the human perception of hearing. Typical valueson this open-ended scale are a sound level of 0 dB, which is the average threshold of human

hearing, and 60 to 70 dB for normal conversation, 110 dB at an extremely loud concert, and

150 dB for the noise of a rocket takeoff or a jet engine at close range.

You can measure the sound pressure level with various weighting filters whose

characteristics approximate the sensitivity of the ear at various frequencies and levels basedon the Fletcher-Munson curves. Most commonly used is the A Weighting, which is most

sensitive in the mid-frequencies. Other, less common weightings are B, C, and D.

The Sound Pressure Level (SPL orLP) in dB is defined as:

SPL = 20 log10(p/pref)

Where p = the actual sound pressure

pref= 20 Pa, which roughly corresponds to the threshold of human hearing


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Important Note: Because of the many factors potentially influencing a decibel reading, be

careful when reporting acoustical data. Without a complete description of all the instrument

settings during the measurement, the information could be ambiguous. A completestatement would include the following elements:

The level as a numeric, as NN.N (Note that one decimal place is sufficient precisionfor almost any test.)

dB for decibels or B for Bels

SPL for sound pressure level, PWL for sound power level, SIL for sound intensity

level

The reference quantity used in the level computation, as appropriate (for example,20 Pa)

Frequency weighting filter used

Time weighting used

Octave or one-third octave band filter used

For example, a complete description of an acoustics measurement is: 85 dB SPL re 20 Pa

A-weighted, Slow, 47 dB PWL re 1 pW flat-weighted in the 250 Hz one-third octaveband, equivalent continuous level.

Units:

Pa or dB re 20 Pa

Free Field

A sound field in a homogeneous, isotropic medium free from boundaries. Waves are

progressive -- that is, the wavefronts spread out continuously in a manner analogous toripples on a pond without reflections.

An anechoic room is a good approximation to a free field. The opposite of a free field is adiffuse field, where multiple reflections result in sound incidence from all directions.

Reverberation Chamber

Room designed to minimize the sound absorption of all surfaces in order to approximate a

diffuse field. Room surfaces are typically concrete or steel.


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Diffuse FieldAn acoustical environment with a high number of reflections -- that is, highly reflective asin a reverberant chamber. At any given point in the diffuse field, sound will arrive from all

angles in a uniform manner.

Sound waves are found to be travelling in all directions simultaneously without preferenceandsound pressure levels are uniform throughout. A diffuse field is the limiting case as

the number of standing waves in a space approaches infinity.

Measurements in a diffuse acoustic field should be made using a random-incidence

microphone.

This term can also be applied to electromagnetic fields.

Octave Band

A band offrequencies extending one octave from 0.707f0 to 1.414f0, wheref0is the band

center frequency. Octave band center frequencies have been standardized by ANSI and

ISO. See 1/N octave.
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