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Bently NevadaThe Plant Asset Management Company SM

Enveloping

Enveloping is an analytical technique that is especially popular for monitoring the condition of Rolling Element Bearings (REBs) using portable data collectors as part of a plant “walk-around” Predictive Maintenance program. It can also be used with permanently installed vibration monitoring instruments.

The basic concept of enveloping is that it demodulates the high-frequency structural “ringing” of a machine in order to extract the repetition rate of impact events that can indicate specific problems with the bearings on the machine. The structural ringing frequency itself is only of interest as a “carrier signal” for the periodic impact information that it contains.

Enveloping is known by several different names within the vibration monitoring industry. A few of the common names are listed here:

- Acceleration Enveloping

- Demodulation

- High Frequency Enveloping

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Presentation Contents

• Introduction– Learning Objectives– Enveloping Definition– Considerations– Typical Applications

• Theory– Repetitive Impacts– The Enveloping Process

• Application– Selecting Filter Settings– Bearing Fault Frequencies

This slide lists the major topics in this presentation.

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Learning Objectives

1. Identify the major steps in the Enveloping Process.

2. Explain how to find a starting point for selecting band-pass filter settings.

3. List and describe the four bearing fault frequencies.

These three Learning Objectives represent major “big ideas” of applying the Enveloping Process.

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Enveloping Definition

• Enveloping is a process that extracts the repetition frequency of periodic impact events from high frequency structural “ringing” of the machinery being monitored.

– Comparing the detected impact repetition frequency with known bearing “fault frequencies” helps you to diagnose the condition of the bearing in question.

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Considerations

• Structural resonance frequencies are attenuated rapidly with distance.

• Temporarily mounting vibration probes may introduce unacceptable variability in the data.

• It is important to collect “baseline” vibration data for trending bearing condition over time.

Enveloping is an indirect process that can be affected by a wide variety of influences. For this reason, no two machines respond exactly the same. It is important to establish appropriate transducer attachment methods and band-pass filter settings for each machine being monitored – and to apply these techniques consistently so that bearing conditions can be trended over time.

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Typical Applications

• Machines containing rolling element bearings:

– Fans– Compressors– Motors– Pumps– etc…

Enveloping is most often used to analyze the condition of rolling element bearings while they are running. This can be done using both portable and online data collection methods.

Accelerometers typically have higher frequency response than velocity sensors, so they are usually better matched to sense the high-frequency structural resonance “ringing” that must be detected in this type of vibration monitoring. This ringing can range from several kHz up to approximately 40 kHz.

The technician in the photo is using a magnetically-attached vibration transducer to collect preliminary measurements on a machine. A temporary mounting such as this provides the flexibility of using many different sampling locations, but it also introduces variability in the collected data. For improved sampling consistency and best signal-to-noise ratio, it is preferable to use a stud-mounted sensor.

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Repetitive Impacts

• Every time a ball rolls over the pit in the bearing race, it causes a tiny “click.”

• These periodic impacts excite the natural resonance frequencies of the machine structure.

“Seismic” vibration transducer (acceleration or velocity)

Defect

This drawing shows a typical rolling element bearing application, with a “seismic” (acceleration or velocity) vibration transducer installed on the outside of the machine housing. The transducer should be installed as close as possible to the bearing of interest, since high-frequency vibration attenuates rapidly as it is transmitted through the machine structure.

The example shows a small defect in the outer race of the bearing. Every time a ball rolls over this defect, it creates a small impact “click” that excites the machine’s natural structural frequency. The repetition frequency of these clicks corresponds to the Outer Race Ball Pass (ORBP) fault frequency.

Note: For any given rolling element bearing, each different type of fault has its own characteristic frequency – based on the specific dimensions and geometry of the bearing components and the rotating speed of the shaft. More information on Bearing Fault Frequencies is included later in this presentation.

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Repetitive Impacts

• With each impact, the machine structure “rings” at its natural resonance frequency.

• These impact events are embedded in a complex vibration signal, and are typically not detectable until they are extracted by the enveloping process.

Periodic impact events

TimeAm

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Typically, the periodic impact pulses are of relatively small amplitude, and are “buried” in the complex vibration waveform. It would be very unusual for them to be visible in the raw vibration signal as clearly as they are shown in this drawing.

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Repetitive Impacts

• The enveloping process allows us to determine the impact repetition frequency.

• Repetition frequency of the impact events corresponds to specific bearing faults.

EnvelopingProcess

Impact RepetitionFrequency

The purpose of the multi-step Enveloping Process is to extract the hidden impact repetition frequency information from the high-frequency structural ringing vibration that is detected by the seismic transducer.

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The Enveloping Process

REPETITIVE DEFECT IMPACT

STRUCTURAL RESONANCE

SEISMIC TRANSDUCER

BAND PASS FILTERING

SPECTRAL ANALYSIS

LOW PASS FILTERING

ENVELOPING RECTIFICATION

DEFECT

REBREB

FREQUENCY

MA

GN

ITU

DE

DemodulationOptional(FFT)

Objective 1

In order to extract the repetition frequency of the impact event, the following steps are performed on the raw waveform signal from the vibration sensor:

Band-pass Filtering: Removes vibration frequencies that are NOT associated with the high-frequency structural ringing. We only want to process the frequencies that correspond to the structural resonances excited by the impact events to be detected.

Demodulation: Converts the AC vibration signal to DC, and removes the high-frequency “carrier” frequencies, leaving an amplitude “envelope” of the original waveform. This is very similar to the way an audio frequency music or voice signal is extracted from a radio-frequency carrier in an AM radio broadcast.

Low-pass Filtering (optional): Removes repetitive events that are above the range of fault frequencies of interest.

Fast Fourier Transform (FFT): Applies an algorithm that detects the component frequencies of the envelope signal – converting the display from the time domain (timebase) to the frequency domain (spectrum).

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Band-pass Filtering Step

• Structural resonance frequencies typically show up as a “haystack” on an unfiltered vibration spectrum. These resonance frequencies act as a carrier of the impact repetition information that we are looking for.

“Haystack”

These are the frequenciesthat we will be processingto extract the impactrepetition information.

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Objective 1

A wealth of machinery diagnostic information is available by traditional direct analysis of the lower vibration frequencies (less than approximately 1000 Hz, in this example). Enveloping intentionally filters out these lower frequencies in order to focus on the structural resonance frequencies in the “haystack.”

Analysis of the lower frequencies is outside the scope of this training module. If you are interested in learning more about vibration analysis, ask your instructor about the Machinery Diagnostics training course.

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Band-pass Filtering Step

• Before demodulation, we will use a band-pass filter to remove frequencies outside of the structural resonance frequencies.

• For clarity, the following slides show the band-pass filtering process as if it were happening in two separate steps.

Example: Structuralresonance between about3100 Hz and 3600 Hz.

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Objective 1

For now, we will assume that appropriate filter settings are already known, and that they are being used by the Enveloping Process. More information on selecting appropriate filter settings is included later in this presentation.

Knowing the approximate structural “carrier” frequency is important for selecting appropriate band-pass filter settings and data collection methods, but not for diagnosing specific machine faults.

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Unfiltered Vibration Signal

• Small periodic impact events are embedded in a complex timebase waveform.

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TimeTime

Objective 1

(idealized data)

This acceleration timebase waveform signal demonstrates how a small, periodic signal can effectively be “hidden” when it is embedded in a complex signal.

This example shows a large amplitude 1X frequency component, idealized as a perfect sine wave, and many high-frequency components. A rotor-related 1X signal such as this might be produced by a simple unbalance condition. Superimposed on this high amplitude signal is a barely-visible low amplitude periodic impact signal occurring at a frequency of just over 6X. The signal also contains some very high frequency vibration, that is well above that of the “haystack” to be analyzed.

Note: The frequency of the ringing “carrier” signal is MUCH higher than the repetition frequency at which the periodic impact events occur.

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High Frequency Filtering

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Time

• High frequencies removed.• Impact events are now visible.

Objective 1

(idealized data)

This example waveform illustrates the same signal from the previous slide after the very high frequency components have been removed. The small periodic impulses are now visible superimposed on the low frequency vibration components.

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Low Frequency Filtering

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Time

• Low frequencies removed.• Amplitude of impact events emphasized.

Objective 1

(idealized data)

This example shows the impact events after the low and high frequencies have been removed by the band-pass filter. It shows that a periodic mechanical impact has generated high-frequency “ringing” at the resonant frequencies of the machine being monitored. The structural ringing caused by each impact decays away after a short time. This decay effect is sometimes called “ring-down.”

Theoretically, it is possible to measure the time intervals between the impact pulses, and determine the fault frequency directly from this time difference:

Frequency = 1 event cycle / time difference between two subsequent events.

Example: For a time difference of 0.01 sec, F = 1 / 0.01 sec = 100 Hz.

However, an actual machine signal is seldom as clean and symmetrical as the idealized signal in this illustration. In real-world applications, it is typically easier to interpret the spikes in the spectrum plot that is created by the final step of the Enveloping Process.

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Rectification Step

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Time

• Rectification changes the negative half of the impact waveform to positive.

Objective 1

(idealized data)

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Enveloping Step

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Time

• Enveloping extracts the “sawtooth” – shaped outline of the rectified waveform.

Objective 1

(idealized data)

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Spectral Analysis Step

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Frequency• Fundamental frequency corresponds to

impact repetition frequency.

Objective 1

(idealized data)

Typically, the harmonic components are a result of processing the sawtooth-shaped waveform with the Fast Fourier Transform (FFT) process, and do not correspond to any real physical vibration effects.

It is possible that more than one bearing fault frequency is present (for example, both Inner Race Ball Pass and Outer Race Ball Pass frequencies). In such a situation, there would be a separate harmonic series for each fault frequency –and the fundamental frequency in each series would correspond to the fault frequency itself.

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Spectral Analysis Step

• Envelope spectrum and raw data spectrum from an actual rolling element bearing that was failing.

• The inner race defect frequency near 66 Hz is modulated by shaft speed, producing ±1X sidebands.

0 50 100 150 200 250 300Frequency (Hz)

0

0.05

0.10

0.15

0.20

0.25

0.30

0.35

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1X Intermediate Shaft

IRPB

IRPB + 1XIRPB – 1X

Harmonics

Envelope Spectrum

Raw Data Spectrum

Actual spectrum

(actual data)

This slide shows a comparison of enveloped spectrum and raw data spectrum from a low speed gearbox. It is interesting to note that the Inner Race Ball Pass (IRBP) fault frequency was detected by the envelope spectrum, but NOT by the direct “raw” spectrum.

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Selecting Filter Settings

• CAUTION – Inappropriate filter settings may mask serious problems.

– Experimentation is usually required until you gain operating experience with your specific machines.

Wrong filter settings (for example, a setting that excludes all structural resonances) may mask serious problems. The difficulty of selecting frequency filter corners lies in the fact that each machine may be different, due to mounting, bearing types, loads, speeds, etc.

Experimentation is often required to find the best frequency range for the enveloping technique to give the best information. Try examining the spectrum of the raw, unfiltered transducer signal to identify “haystacks” associated with structural resonances.

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Selecting Filter Settings

• As a starting point, look for a high frequency “haystack” in the spectrum of the raw, unfiltered transducer signal to identify structural resonance frequencies.

“Haystack”

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Objective 2

The low frequency corner of the band-pass filter is generally set to about 50 times rotor speed or 3 times gear mesh, not to exceed 1 – 2 kHz. However, this corner should not exceed one-half the expected structural resonance frequency as this is the carrier frequency excited by the defect impacts.

The high frequency corner of the band-pass filter should be set to a frequency high enough to include structural resonance frequencies and low enough to exclude the transducer mounted resonance frequency. A good starting point might be 10 kHz. Remember that some accelerometers can amplify vibration signals by a factor of 20 or more at the mounted resonance. The filter corner should be set low enough to provide adequate attenuation of these very highly amplified signals.

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• Select band-pass filter settings that include the resonance frequencies.

• Example settings:– 400 to 2000 Hz (too low)– 800 to 4000 Hz– 1600 to 8000 Hz– 3200 to 16,000 Hz (maybe)– 6400 to 32,000 Hz (too high)

Selecting Filter Settings

Example: Structuralresonance between about3100 Hz and 3600 Hz.

Objective 2

In this example, two band-pass filter settings appear to be the best candidates for initial data collection.

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Bearing Fault Frequencies

• Calculated from bearing parameters and machine running speed:

– Number of elements– Element diameter– Pitch diameter– Element contact

angle– Shaft RPM

This slide shows the basic components of a typical Rolling Element Bearing (REB).

By knowing the dimensions and arrangements of these REB components, it is possible to calculate expected “fault frequencies” associated with various bearing problems.

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Bearing Fault Frequencies

• ORBP = Outer Race Ball Pass Frequency

• IRBP = Inner Race Ball Pass Frequency

• BSF = Ball Spin Frequency

• FTF = Fundamental Train Frequency

Frequency (Hz)

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Example: Conrad type 214 radialball bearing running at 3550 RPM

Objective 3

ORBP – Indicates outer race defects.

IRBP – Indicates inner race defects.

BSF – Indicates rolling element spalling.

FTF – Indicates cage defects.

Inner and outer ball pass frequencies are caused by rolling elements as they pass over a flaw on the inner or outer race. The inner and outer ball pass frequencies can be calculated directly from the bearing geometry, if there is no slippage or dimensional change with load.

The fundamental train frequency, also known as the “cage frequency,” is the frequency at which the rolling elements revolve as a set. It is less than one-half rotor speed on bearings with a stationary outer race. Any combination of flaws can generate, or be modulated by, the fundamental train frequency.

Ball spin frequencies are caused by rolling element flaws or a defect in the cage. A flaw in a ball can generate frequencies at twice the ball spin frequency, by impacting both the inner and outer races with each rolling element rotation.

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−Ω= αcos1120 D

dNORBP

Bearing Fault Frequencies

ElementDiameter

Shaft (inner race)Rotation Speed

Element ContactAngle (alpha)

Pitch Diameter is the diameter of the centerline of the rolling elements.

Number ofElements

This example is just one out of an entire family of equations that are used to calculate fault frequencies produced by defects in a rolling element bearing.

This version of the ORBP equation only applies for the following specific conditions:

-Outer race is fixed and the inner race rotates (most commonly-encountered arrangement for typical rotating machinery, such as electric motors).

-No slip between the rolling elements and the races.

Other versions of the equation include terms for rotation speed of both the inner and outer races, and for slippage between the rotating elements and the races.

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Bearing Fault Frequencies

• Using software can help avoid manual computation errors, but it is still just as important to use the correct bearing parameters and machine running speed. Software calculator example

This software calculator example is based on a fictitious ball bearing with the Parameters shown above.

The Fault Frequencies are calculated as nX “orders” (multiples) of shaft rotation speed even before the shaft RPM is entered. But for the calculator to convert these nX orders to Hz, it must also have the RPM information.

Note: Since rolling element bearings are typically replaced as a single assembly, it is often only of academic interest to determine which of the specific fault frequencies were detected. For example, it does not really matter whether it is the inner race or the outer race that is damaged. If EITHER race is damaged significantly, it may be appropriate to replace the bearing.

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Bearing Fault Frequencies

• Once you have detected impact repetition frequencies, you can compare them with known fault frequencies for the bearing being monitored. “It looks like we’re seeing a big

increase in IRBP frequencies on this bearing. It might be time to talk with the Maintenance Department…”