Peak Vue

PeakVue

“ONE STEP IN YOUR JOURNEY TO BENCHMARK STATUS”

PEAKVUE

WORLD HEADQUARTERS835 Innovation DriveKnoxville, Tennessee 37932Phone: (423) 675-3200Fax: (423) 675-3205

SAN DIEGO TRAINING CENTER4180 Ruffin Road, Ste. 115San Diego, California 92123Phone: (619) 571-8882Fax: (619) 571-8887

HOUSTON TRAINING CENTER15425 North Freeway, Ste. 160Houston, TX 77090Phone: (281) 873-6000Fax: (281) 873-6633

DETROIT TRAINING CENTER39830 Grand River Ave. Ste. B-1-ANovi, Michigan 48376Phone: (248) 426-0472Fax: (248) 426-0574

“ONE STEP IN YOUR JOURNEY TO BENCHMARK STATUS”Copyright 1997, Computational Systems Incorporated. All rights reserved. Content for this manual provided by CSI Training Instructor(s).Formatting and editing by M. Angela West.

0997

Table of Contents! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

Section Title

1 Introduction to PeakVue

2 Digital Signal Processing

3 Case Histories and Applications

Appendix A PeakVue Data Collection Techniques for the RBMAnalyst

Appendix B An Improved Methodology for Defect Detection inGear Boxes

Section OneIntroduction to PeakVue

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

PeakVue TrainingIntroduction to PeakVue

1-2 © Copyright 1997, Computational Systems Incorporated. All rights reserved.

Objectives! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

1. Comprehend the different uses of PeakVue techniques.

2. Have a basic understanding of PeakVue processing

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

IntroductionThis section presents the background information and PeakVue techniques. PeakVueprocessing is proving to be the preferred technique for detection of machine defects intraditionally difficult applications. This processing has been effective in both slow speedand high speed applications, typically far earlier than routine spectral and waveformvibration data collection.

PeakVuePeakVue stands for peak value and can be used to detect short duration higherfrequency waves called stress waves. Stress waves are created when metal is bent,impacted, cracked or scuffed. For example, if a rolling element in a bearing passesover a defect which may still be below the surface of the inner or outer race, the racewill deflect and then spring back. This motion will create a sine wave. This sinewave, or Stress Wave will have the following characteristics:

Y Short term transient - a few millisecondsY High frequency - 1kHz to 50 kHz

PeakVue measures the highest amplitude found in this waveform and holds it as thehighest value during a waveform time length equal to 1 over the sampling rate. PeakVue also passes the waveform data through a high pass filter to removeunwanted high amplitude vibration frequencies from the data. The high pass filtershould be set above the conventional Fmax of the spectrum.


© Copyright 1997, Computational Systems Incorporated. All rights reserved. 1-3

FiltersThe PeakVue gives you the option of two types of filters:

• Band Pass• High Pass

Each one filters data out of a signal, which you may find useful when analyzingsignals with large dynamic ranges. For example, some spectra have both large andsmall amplitudes relative to each other. Because of the dynamic range of theanalyzer, however, you cannot analyze the low amplitude vibration in the same plot asthe high amplitude vibration. A filter helps resolve the problem.

Dynamic RangeDynamic range is defined as the ability of the analyzer to distinguish between thehighest and lowest amplitude signals. It is controlled by the Analog to Digital (A/D)processor. The 2120 has a greater than 90 dB dynamic range. Decibel (dB) units areused because the logarithmic scale makes it easier to describe numbers that are verylarge and very small with the smaller numbers. Filters can increase the effectivedynamic range by omitting frequencies of high amplitude, allowing the loweramplitude signals to be shown.

Band-Pass Filter

There are two types of bandwidth filters S Constant Percentage Bandwidth andConstant Bandwidth. These filters primarily serve the same function. PeakVue canutilize the constant bandwidth type filters of: 20-150 Hz,50-300 Hz, 100-600 Hz, and500-1,000 Hz.



Notice the difference between the two types of filters in the example above. Asshown, the filter to choose is the Constant Bandwidth Filter, because it provides thebest resolution between both high- and low-frequency components.

High-Pass Filter

The high-pass filter gives you the ability to filter out low-frequency components fordetailed analysis as illustrated above. This proves useful when low-frequency, high-amplitude data swamps the high-frequency, low-amplitude data you want to see. Thissituation often occurs when high-frequency events appear in the same plot as RunSpeed and its related harmonics.

Selection of the high pass filter frequency filter is the most important considerationwhen using PeakVue. The goal of the filtering process is to remove the rotationalvibration frequencies such as turning speed harmonics, bearing frequencies, multiplesof gear mesh frequency, etc. The high pass filter should be selected to remove theserotational frequencies. Therefore, select a filter above the highest operational or defectfrequency that you can estimate.

Although the information we are looking for is lower frequency in nature, we want touse acceleration as our data analysis unit.



Data taken without PeakVue enabled.

Data taken with PeakVue enabled.

Generally, the 1000-Hz high pass filter is a good choice. The PeakVue process altersthe length of short-duration, very high-frequency events occurring in a machine’svibration data. Be sure to set up a measurement point that uses an accelerometerand does not integrate the data

Measurement ConsiderationsKeep in mind that the PeakVue reading is really a high frequency measurement evenon low speed equipment. The following are recommendations for makingmeasurements.

Y Use an accelerometer with a high frequency response (>5kHz)Y .100 volts per G acceleration preferred (.500 volt/G not recommended)Y Rare earth, flat magnet or stud mount (2 pole magnet not recommended).Y Flat, metal to metal contact between accelerometer and machine being measured ,

no paint or dirt.Y Use a coupling agent between metal interfaces (bee’s wax, grease)



2120 SetupPeakVue can be accessed from the 2120 Acquire Spectrum Menu.

Y FREQUENCY Chosen as in normal analysisThe actual frequencies are limited to the following in PeakVue:

20 Hz, 50 Hz, 100 Hz, 200 Hz, 400 Hz, 500 Hz, 1kHz, 2kHz and 5khz.

Y LOW CUTOFF Normally 0 (zero)

Y LINES 1600 for trending, 3200 for problem diagnosis

Y AVERAGES 4-6 is fine

Y SST CONTROL Set to NO

Y UNITS/INTG Acceleration/Analog- This keeps the units in G’s.The integration method then has no effectbecause we are not integrating (acceleration<-----acceleration. )



Toggle to the third page of the setup menu.

Y DEMODULATE Set to NOY PEAKVUE Set to YESY PREFILTER Choices are: 500, 1000, 2000, 5000, 10kHz and

20kHz High Pass or 500-1000 Hz Band Pass.

Collection of at least one data point per machine component is recommended usingthe PeakVue technology for early detection of bearing and gear defects, shaft to sealrubs, torsional vibration as well as other machine problems. For machines that run atless than 600 RPM, PeakVue should begin to replace normal processing for allreadings.



MasterTrend SetupThis can also be activated from a MasterTrend Analysis Parameter Set definition. Onetechnique is to setup many “generic” PeakVue sets and modify them as needed.



In this database, nine sets have been created. The names explain the FMAX and HighPass filter.



This set may be used for a shaft speed less than .5 Hz (30 RPM).

The Signal Processing Parameters tab is where PeakVue is enabled. The high passfilter is chosen to be above the FMAX . The selection of the HP filter is based on thedesired elimination of any unwanted frequencies to increase dynamic range.



A measurement point must be setup to store the PeakVue data.

The Units Type Code should be set to Accel<---------Accel. Analysis Parameter set 19is an appropriate choice for this point.



The second tab contains the sensor and signal information

Sensor Sensitivity (V/EU) should be 0.1. A high frequency accelerometer isrecommended. Add the point to a Route and you are ready to collect PeakVue data.

Summary

This technique is very powerful as a diagnostic tool and early detection method. Inthis section, we have examined the setup and considerations for PeakVue as well asmethods of enabling this feature from both the 2120 Machinery Analyzer andMasterTrend.

Section TwoDigital Signal Processing

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

PeakVue TrainingDigital Signal Processing

2-2 © Copyright 1997, Computational Systems, Incorporated. All rights reserved.

Objectives! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

Y Relate time waveform length and frequency bandwidth to sampling rate andsample size.

Y Choose the correct analysis window for each vibration analysis opportunity.

Y Recognize limitations of digital signal processing.

Y Have the ability to use the 2120 analyzer and the Analyze function toacquire data utilizing PeakVue®.

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

Fast Fourier TransformThe conversion of time domain information to frequency domain information isthe Fast Fourier Transform (FFT).

Often a frequency spectrum is referred to as an FFT. However, the FFT is themathematical conversion from the time domain to the frequency domain. Sincethe signal that comes into the analyzer is an analog signal as discussed in theprevious section, it must be digitally sampled by the analyzer. Therefore, theprocess used by digital analyzers is actually a variation of the FFT, called theDiscrete Fourier Transform (DFT).


© Copyright 1997, Computational Systems, Incorporated. All rights reserved. 2-3

Instantaneous Sampling-Normal Processing

For the DFT, the time waveform is recreated in the analyzer by digitallysampling, and then it is transformed into the frequency domain. The FFTprocess works based on the assumption that the signal measured and digitallysampled is one period of a periodic signal that extends to minus infinity and toplus infinity. Normally, this is true for most vibrating pieces of equipment.

It is the digital sampling process that makes the signal processing morecomplicated. The information here unlocks the mysteries of digital signalprocessing without getting bogged down in too much theory.

In order to understand the FFT digital sampling process, you must understandthe relationship between lines of resolution (LOR), maximum frequency (Fmax),length of time waveform (Tmax), the digital sample size, filters, and unitconversion.



ResolutionOnce data has been converted to the frequency domain from the time domain,view all the frequencies of interest in as much detail as possible. Resolution isthe number of parts of the spectrum, usually called lines of resolution (LOR). The number of lines of resolution selected are divided into the maximumanalysis frequency (Fmax) to arrive at the bandwidth (BW).

BW = Fmax/LOR

The lines are actually the center frequencies of what are often called bins ofenergy. Each bin actually contains an infinite number of frequencies, and allthe energy in the bin is summed and represented by a single amplitude at thecenter frequency identified at each line of resolution.

First, identify your frequencies of interest so that enough resolution is chosen toseparate closely spaced frequencies. A common L.O.R. for PeakVue is 1600lines. Also, be aware that more lines of resolution affect the length of the timewaveform. For normal trending, we have to weigh the pros and cons of higherresolution. Remember that the time to collect one average is equal to 1 dividedby the bandwidth. As the bandwidth decreases, the data collection timeincreases The bandwidth (BW) should be no greater than 5 HZ/Line.



This will give adequate resolution for identifying trend changes and reasonabledata collection time.One popular way of setting Fmax is to use an order based set based on turningspeed of the shaft being monitored. Let’s take a look at the effect of RPM onthe Sample Rate with a typical 70 x Turn Speed Rolling Element BearingSet:

The drawing above represents the sampling of instantaneous values to representa sine wave. This is fine when the sampling rate is high enough relative to thefrequency being sampled. As the bandwidth or Fmax is lowered, the samplingrate decreases and can not accurately represent a high frequency, transientevent such as a stress wave.

PeakVue samples a time interval for a maximum value at the maximumsampling rate independent of the bandwidth. Even very low Fmax settings arestill able to capture a peak event from stress waves.



Sampling Rate Limitations-Normal Processing

RPM x 70= Fmax

* 2.56=SampleRate

60 HZ (3600 CPM) 4,200 10,752/sec.

20 HZ (1200 CPM) 1,400 3584

1 HZ (60 CPM) 70 179

If the time window is held constant at .01 seconds, an Fmax of 4200 hz wouldgive 107 samples (10,752 ÷ 100). PeakVue would take the above timeincrement, sample it at 100,000 samples per second, independent of the Fmax.

The highest value would be “captured” for processing. Transient events, likethose produced in stress waves from defects or impacting in metal are easilydisplayed.



Sampling Rate Example - PeakVue Processing

PeakVue, through some elaborate signal processing, captures high frequency,transient events, extends them in time and processes this signal for the timewaveform and for FFT processing of the spectrum. The real amplitude iscaptured, so unlike other forms of processing, like Demodulation, this valuecan be trended.



Time Record LengthCalculate the time record length of the time waveform, Tmax, from the followingbasic relationship.

Tmax = 1 / BW

or

Tmax = LOR/Fmax

At face value, this is a simple and often used equation. However, to understandthe limitations of some analyzers, it is important to more fully investigate therelationship between the Fmax, the LOR, and the Tmax.

Tmax = sample size / sample rate

Sample size = 2.56 * Lines of Resolution

Sample rate = 2.56 * Fmax

These terms have already been defined, but be aware that some analyzers havean upper limit on the sample size. In the 2120, this number is 4,096.Therefore, a 400-line spectrum would require 2.56 * 400 = 1,024 samples, a800-line spectrum would require 2.56 * 800 = 2,048 samples, a 1600-linespectrum would require 2.56 * 1600= 4096 samples and a 3200-line spectrumwould require 2.56 * 3200= 8,192 samples. However, if the analyzer is limitedto 4,096 samples, then the 3200-line spectrum will be created from 4,096samples since it is the upper limit of the analyzer. This is important whendiscussing the Tmax in the time waveform, because, in general, raising the Fmaxdecreases Tmax, and raising LOR increases Tmax to the point that the multiple of2.56 * LOR reaches the sample limit in the analyzer. In this case, the samplesize for anything greater than 1600 lines is forced to be 4,096.



The table below demonstrates how this limitation affects the Tmax for amaximum 4,096 sample size analyzer.

Tmax = sample size / sample rate

Fmax Sample Rate (Sr) =Fmax*2.56

L.O.R. Sample Size (Ss)=L.O.R.*2.56

Time (sec.)=Ss ÷ Sr or

LOR ÷ Fmax

400 1024 400 1024 1.00

400 1024 800 2,048 2.00

400 1024 1600 4,096 4.00

400 1024 3200 8,192( 4,096 stored by

MT))

8.00(4.00 storedby MT)

The last entry in the table may seem incorrect, but remember 4,096 is themaximum sample size, and anything that would be greater than 4,096 is forcedto be 4,096 for storage in MasterTrend. This is the reason your time waveformis not affected when following the raise-the-LOR-to-lengthen-the-time-waveform rule. You must be aware of the upper limit of the sample size andthe number of lines of resolution to which this number corresponds. Toincrease the amount of time in the time record, it will become necessary toadjust the Fmax to a lower value. The following chart show the effect on the timerecord of various Fmax settings.

Fmax (Hz) Sample Rate (Sr) =Fmax*2.56

L.O.R. Sample Size (Ss)=L.O.R.*2.56

Time (sec.)=Ss ÷ Sr or

LOR ÷ Fmax

1000 2560 1600 4096 1.6

400 1024 1600 4096 4

200 512 1600 4096 8

100 256 1600 4096 16

10(low freq.

limit)

25.6 1600 4096 160 (maximumstored by MT)

10 25.6 3200 8192 320 (160 storedby MT)

Integration and Differentiation



The vibration data that is the input signal into the analyzer is a time-varyingvoltage proportional to the vibration measured by the transducer. In otherwords, an accelerometer produces a voltage that varies over time relative to theacceleration measured by the transducer. The voltage amplitude in the timewaveform is converted to the desired amplitude units based on the sensitivityand conversion factor of the transducer.

Most analyzers have the ability to convert from the measurement units of thetransducer to either of the other two units in the time domain or the frequencydomain. At CSI, integration of the time signal is called analog integration andintegration of the frequency domain is called digital integration.

Integration is a process of converting from acceleration to velocity ordisplacement, or converting from velocity to displacement.

Differentiation is the process of converting from displacement to velocity oracceleration, or converting from velocity to acceleration.

How are these unit types related, mathematically?

D (Displacement) = distance traveled by vibrating objectV (Velocity) = change in Displacement/change in Time A (Acceleration) = change in Velocity/change in Time

These terms are often represented with the following equations:

D = XV = X / T

A = X / T / T = V / T

Therefore, if any one of these terms has been measured, integration anddifferentiation allows any of the other terms to be calculated, provided theanalyzer or software used is capable of this conversion process.

One drawback to integration is a flare-up of the lower frequency data caused bythe integration process. This effect is often called integration noise or a ski-slope effect. This very noticeable when integrating from acceleration to velocityin PeakVue and tends to affect only the lower 1% of the frequencies. This maycause the overall vibration level to be higher than usual, and it may be excludedfrom the calculation of the overall vibration level.

Summary



This section has introduced some signal processing basics. A clear understandingof signal processing may help the analyst when making decisions on how to setupa vibration data collection point. PeakVue is a unique process, with great power inmany applications.

Section ThreeCase Histories and Applications

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

PeakVue TrainingCase Histories and Applications


900 HP300 RPMSynchronous Motor

Wood ChipperSKF 23156C double row sperical roller bearings

Objectives! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

Y Use PeakVue in multiple applications.

Y Choose the correct setup for each vibration analysis opportunity.

! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

Case History - Chipper Bearing

This equipment is in a large papermill. The chipper is fairly slow speed and runs24 hours a day. The equipment was on a normal vibration route.



WAVEFORM DISPLAY 04-APR-97 10:02 RMS = .0516 PK(+) = .3759 PK(-) = .2328 CRESTF= 7.28

0 100 200 300 400 500 600 700 800

-0.3-0.2-0.1-0.0

0.10.20.30.40.5

Time in mSecs

Acc

eler

atio

n in

G-s

2WYD - #2 CHIPPER CH-1132-01-02 -CIA CHIPPER INBOARD AXIAL

ROUTE SPECTRUM 04-APR-97 10:02 OVRALL= .0455 V-DG PK = .0455 LOAD = 100.0 RPM = 301. RPS = 5.01

0 100 200 300 400 500

0

0.006

0.012

0.018

0.024

0.0300.036

Frequency in Hz

PK V

eloc

ity in

In/S

ec

The normal data is shown below. The relatively low amplitudes in both thespectrum and waveform would not have alarmed automatically.

The analyst suspected a bearing problem and decided to setup to take PeakVuedata. Notice the impact level in the waveform is only .6 G’s Pk-Pk. The real levelwill be shown later. With a 500 hz Fmax the sample rate is 1,280 samples/sec.Utilizing the Analyze function, additional data was stored.



PeakVue SetupThe setup of PeakVue is flexible, so the analyst should not feel intimidated whenusing it. Many “incorrect” setups will still give good data. The choice of Fmax andthe High Pass Filter follow some basic rules.

Setting Fmax For rolling element bearings:Y Use 3-10 times the inner race frequency (BPFI)Y If you do not know the BPFI, 10 times running speed is a good

estimate for large (> 6” diameter), in this case 50 HZ.

In this case the running speed is 300 RPM or 5 HZ. Then, 3-10 times would yieldan Fmax of anywhere in the range of 150-500 HZ. The “correct” Fmax would havebeen 500 HZ. Remember, don’t get too worried about being exact, PeakVue isforgiving!

Setting the HP Filter:

Y Choose the next filter above FmaxY Set filter above high G level vibration (running speed harmonics,

cavitation, gear mesh etc.)




Analyze Spectrum 04-APR-97 10:04 (PkVue-HP 2000 Hz)

RMS = 1.26 LOAD = 100.0 RPM = 300. RPS = 5.01

0 20 40 60 80 100

0

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Freq: Ordr: Spec:

2.221 .443 .311

The analyst chose a 100 HZ Fmax . The high pass filter should be the next filteravailable above Fmax . The filter could have been 500hz, 1Khz, 2Khz, 5Khz,10Khz, or 20Khz. He chose 2Khz. With the filter we are trying to increase thedynamic range of the equipment by filtering out any high G levels that wouldinterfere with stress wave processing. If there are high G levels near 1000hz, setthe filter at 2000hz.The results are shown.

The highest amplitudes in the axial direction are at the Fundamental TrainFrequency (FTF). The cage is impacting, but how high is the real amplitude?The waveform reveals what the normal processing was missing.




Waveform Display 04-APR-97 10:04

RMS = 1.55 LOAD = 100.0 RPM = 300. RPS = 5.01

PK(+) = 17.26 PK(-) = .8885 CRESTF= 11.16

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

-2

0

2

4

6

8

10

12

14

16

18

20

Time in Seconds

Acc

eler

atio

n in

G-s

Time: Ampl:

2.246 -.409

Approximately 20 revolutions of the shaft are show (5 rev/sec. Times 4 seconds).Impacts as high as 18 G’s are shown.





RMS = 1.84 LOAD = 100.0 RPM = 300. RPS = 5.01

PK(+) = 17.26 PK(-) = .8885 CRESTF= 11.16

0.4 0.6 0.8 1.0 1.2 1.4 1.6

-2

0

2

4

6

8

10

12

14

16

18

20

Time in Seconds

Acc

eler

atio

n in

G-s

Time: Ampl:

1.094 17.33



RMS = 2.09 LOAD = 100.0 RPM = 300. RPS = 5.01

PK(+) = 17.26 PK(-) = .8885 CRESTF= 11.16

800 900 1000 1100 1200 1300 1400

-2

0

2

4

6

8

10

12

14

16

18

20

Time in mSecs

Acc

eler

atio

n in

G-s

Time: Ampl: Dtim; Freq:

1093.8 17.33 .00000 .00000

>SKF 23156C C=BSF : 20.51

C C C C C C C C C C C

If we look closer, we can see multiple impacts at every other revolution of theshaft.

The Fault Frequency lines line up on the 1x BSF (ball spin frequency). We actuallyhave peaks in between signifying 2x BSF This signifies 2 defect areas, 180degrees on one roller.



The roller shows heavy electrical fluting. The same pattern appeared 180 degreesapart on the other side of the roller. Fluting can occur due to a number of causes.Basically it is a voltage discharge through a bearing. This can occur due to staticbuildup and discharge or when a welder uses the machine for ground whenwelding a shaft. These defects were clearly seen in PeakVue spectrum andespecially the time waveform.

MasterTrend SetupTo setup this machine as a route point, the following screens should be followed.



Add a measurement point called CPA, Chipper PeakVue Axial . This sphericalroller bearing shows defects in the axial direction best.



Choose the appropriate Analysis Parameter (AP) set. Using the rules from earlier:

Fmax = Shaft speed * 10 (inner race approx.) * 5 (orders)

Fmax = 5 Hz * 10 * 5

Fmax = 500 Hz



Steam Turbine/Generator 220 MW

ReductionGears

GeneratorExciter

4 : 1 R e d u c t i o n G e a r

G 7 A / P 7 A

G 8 A / P 8 A

Measurement Points for Gears

Case History - Pinion Gear on Generator

This equipment is in a large electric generating facility. The turbine turns at 3600RPM and has a pinion gear to a larger gear. This turns the exciter for thegenerator.



PKY9 - TURBIN GENERATOR SLEEVETUR-GEN -G7A EXCITER GBOX INBOARD INPUT AXIAL

Route Spectrum 28-MAY-97 10:09

OVRALL= .1068 V-DG PK = .1064 LOAD = 45.0 RPM = 3586. RPS = 59.77

0 1000 2000 3000 4000 5000

0

0.02

0.04

0.06

0.08

0.10

Frequency in Hz

PK V

eloc

ity in

In/S

ec

Freq: Ordr: Spec:

1494.2 25.00 .06725

>PIC PICGEN A=Grmesh(1>2) : 1500.

A A

Input Shaft 1x

Gearmesh

The normal data is shown below for G7A, gearbox input shaft, inboard side.

The gearmesh and sidebands made the analyst decide to use PeakVue to get abetter look.

Setup for GearsTo setup PeakVue for gearboxes here are a few rules:

Setup 2 points at each bearing location.

Y One high frequency (3.5 times gearmesh, 3200 lines to look atgearmeshing problems). Set the high pass filter above the Fmax.*Note: This reading may be extremely high frequency, use theappropriate accelerometer and mounting.

Y The other point should be setup for the bearing and lower order shaft information at 25-50 orders of the shaft speed



To set the points up in MasterTrend:

Choose the appropriate AP set. The first point would be setup as the lowerfrequency. This is a sleeve bearing, so no bearing information is needed. We willbe concerned with shaft turning speed harmonics. Choose the Fmax to be 10-15times turning speed. The input shaft is 60 Hz * 15 = 900 Hz, so choose the 1,000Hz set.

The second point is the high frequency point at 3.5 times gearmesh. Gearmesh is ataround 1,600 Hz, 3.5 *1600 is 5,600 Hz. Choose the 5,000 Hz Fmax set with 5,000Hz high pass filter.



Alarm Limits

Setting Alarm Limits (AL) on PeakVue points may have to be done manually witha different AL set for each point. Experience with different machines andhistorical data may be the best guides. Operational characteristics as well as theFmax and High Pass Filter Settings will also have to be taken into consideration.The first time a PeakVue reading is taken, we may assume that the machine is ingood condition (the majority of machines are not in failure - we hope!).




0 10 20 30 40 50 60 70 80

-0.12

-0.06

0

0.06

0.12

0.180.24

Time in mSecs

Acc

eler

atio

n in

G-s

PKY9 - TURBIN GENERATOR SLEEVETUR-GEN -P7A EXCITER INBOARD PeakVue

ROUTE SPECTRUM 03-APR-97 12:49 (PkVue-HP 5000 Hz) OVRALL= .0188 A-DG RMS = .0187 LOAD = 100.0 RPM = 894. RPS = 14.89

0 1000 2000 3000 4000 5000

0

0.002

0.004

0.006

0.008

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Using this as a baseline, we can set an alarm at 100-300 percent of the baseline asa guideline .

Considerations for Alarm Limits in PeakVue

Y Historical dataY Operational characteristics of the machineY Fmax and High Pass Filter Settings

The Peak-Peak waveform alarm and Overall spectrum alarm may be the bestalarms to start out with. The set below was chosen based on the baseline data.

The baseline data shows very low levels in both the spectrum and waveform.This gearbox shows no major defects, so a generic AL set is made.



Gearbox Alarm Limits

YYYY Use reference data (assuming machine is in good shape)Y Waveform Pk-Pk Alert: 2 G’s ; Alarm: 4 G’sY Overall Spectrum Alert: .1 G ; Alarm: .3 G’s




0 10 20 30 40 50 60 70 80

-2.5-2.0-1.5-1.0-0.5

00.51.01.52.0

Time in mSecs

Acc

eler

atio

n in

G-s

ALERT

ALERT

FAULT

FAULT

PKY9 - TURBIN GENERATOR SLEEVETUR-GEN -P7A EXCITER INBOARD PeakVue

ROUTE SPECTRUM 03-APR-97 12:49 (PkVue-HP 5000 Hz) OVRALL= .0188 A-DG RMS = .0188 LOAD = 100.0 RPM = 894. RPS = 14.89

0 1000 2000 3000 4000 5000

0

0.02

0.04

0.06

0.08

0.100.12

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Freq: Ordr: Spec:

3074.2 206.42 .00017

Alert Limit

ConclusionsIn this case history, the normal spectrum and waveform information showedpossible gear mesh problems with high GMF with sidebands. This has always beenconsidered a indicator of wear and/or broken teeth. PeakVue refuted thatconclusion by showing that no major impacting or micro welding of metal wasoccurring. These gears were inspected with no abnormal wear conditions found.The high GMF and sidebands of the pinion and bull gear running speed werefound to load related. At lower loads, the gears were backlashing creatingamplitude and frequency modulation. The modulation was reflected by thesidebands of run speed around GMF in the spectrum. This caused the spectrumdata to appear in alarm.



Case History - Reciprocating Compressor

Reciprocating Compressor

200 HP 1775 RPM Motor Piston

Crankshaft345 RPMDouble Row

Spherical Roller Brgs318448

Reciprocating compressors present many challenges from a vibration analysisstandpoint. The large forces due to the movement and compression of the piston(1x, 2x RPM) often “drowns out” the lower amplitude level bearing faults. Thefiltering feature of PeakVue was used to increase the dynamic range and attenuatethe forces of the reciprocating vibration.



PRAX - NITROGEN COMPRESSORNITROGEN -CIA COMPRESSOR INBOARD BEARING AXIAL

Route Spectrum 01-OCT-97 11:46

OVRALL= .4472 A-AN PK = .0946 LOAD = 100.0 RPM = 346. RPS = 5.77

0 60 120 180 240 300

0

0.02

0.04

0.06

0.08

0.10

0.12

Frequency in Hz

PK V

eloc

ity in

In/S

ec

Freq: Ordr: Spec:

5.625 .975 .03228

Normal Processing

The spectrum is dominated by running speed harmonics. Looseness may besuspected. This is somewhat normal for reciprocating machines. PeakVue wasutilized to determine the severity of the looseness.




Analyze Spectrum 01-OCT-97 11:46 (PkVue- HP 500 Hz)

RMS = .2045 LOAD = 100.0 RPM = 347. RPS = 5.78

0 60 120 180 240 300

0

0.02

0.04

0.06

0.08

0.10

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Freq: Ordr: Spec:

5.781 1.001 .06494


Analyze Spectrum 01-OCT-97 11:46 (PkVue- HP 500 Hz)

RMS = .2045 LOAD = 100.0 RPM = 347. RPS = 5.78

0 60 120 180 240 300

0

0.02

0.04

0.06

0.08

0.10

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Freq: Ordr: Spec:

47.34 8.195 .04590

>KOY JHM318448/10 C=BPFO : 46.83

C C C C

PeakVue Processing

PeakVue shows harmonics of running speed signifying there is impacting metal asthe shaft rotates, not just reciprocating forces. In addition, some non-synchronouspeaks begin are also now visible.

The outer race and inner race (BPFO, BPFI) fault frequencies are visible,signifying faults in the crankshaft bearings. They were lost in the noise in normalprocessing.




Analyze Spectrum 01-OCT-97 11:49 (PkVue-HP 1000 Hz)

RMS = .1572 LOAD = 100.0 RPM = 347. RPS = 5.79

0 60 120 180 240 300

0

0.02

0.04

0.06

0.08

0.10

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Freq: Ordr: Spec:

62.50 10.80 .01953

>KOY JHM318448/10 D=BPFI : 63.01

D D D


Waveform Display 01-OCT-97 11:49

RMS = .1947 LOAD = 100.0 RPM = 347. RPS = 5.79

PK(+) = 1.01 PK(-) = .4237 CRESTF= 5.20

0 0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4 2.7 3.0 3.3

-1.0

-0.8

-0.6

-0.4

-0.2

-0.0

0.2

0.4

0.6

0.8

1.0

1.2

Time in Seconds

Acc

eler

atio

n in

G-s ALERT

ALERT

FAULT

FAULT

Time: Ampl:

1.599 -.190

The waveform shows 1 G impacting, a moderate fault. The bearing was reportedas being in stage 3 of bearing failure due to the high number of harmonics in thespectrum and levels in the waveform.



ConclusionsThe filtering feature of PeakVue was used to eliminate a large amplitude vibration,increasing the dynamic range so lower amplitudes could be seen. The metalimpacting caused stress waves identifying severe looseness in the bearings. Thebearings were changed and found to be loose and have significant eye visiblefaults.



Case History - High Speed Grinding Spindle

High Speed Grinding Spindle

3600 RPMWheel Motor

15-18,000 RPMWheel Grinder

This spindle grinder grinds the race of a wheel bearing. The high speed bearingsare oil mist lubricated. High speed bearings need to be monitored on a morefrequent schedule because minor defects can progress into major defects quickly.



WAVEFORM DISPLAY 05-MAR-97 13:46 RMS = .0853 PK(+) = .3515 PK(-) = .1906 CRESTF= 4.12

0 10 20 30 40 50 60 70 80

-2.5-2.0-1.5-1.0-0.5

00.51.01.52.0

Time in mSecs

Acc

eler

atio

n in

G-s

CF ALARM

CF ALARM

PK ALARM

PK ALARM

GRND - D18 WHEELD18 WHEEL -VOH SPINDLE OH D18 PEAKVIEW

Label: Good condition

ROUTE SPECTRUM 05-MAR-97 13:46 (Filtr- HP 600 Hz) OVRALL= .0789 A-DG RMS = .0788 LOAD = 20.0 RPM = 15152. RPS = 252.54

0 1000 2000 3000 4000 5000

0

0.02

0.04

0.06

0.08

0.10

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

Freq: Ordr: Spec:

252.54 1.000 .00706

Progression of Fault

When the spindle is in good condition, the levels are low in both the spectrum andwaveform.



WAVEFORM DISPLAY 23-APR-97 18:03 RMS = .8030 PK(+) = 4.41 PK(-) = 1.04 CRESTF= 5.49

0 10 20 30 40 50 60 70 80

-6

-4

-2

0

2

46

Time in mSecs

Acc

eler

atio

n in

G-s

CF ALARM

CF ALARM

PK ALARM

PK ALARM

GRND - D18 WHEELD18 WHEEL -VOH SPINDLE OH D18 PEAKVIEW

ROUTE SPECTRUM 23-APR-97 18:03 (Filtr- HP 600 Hz) OVRALL= .6731 A-DG RMS = .6693 LOAD = 20.0 RPM = 15209. RPS = 253.49

0 1000 2000 3000 4000 5000

00.050.100.150.200.250.300.350.40

Frequency in HzR

MS

Acc

eler

atio

n in

G-s

Freq: Ordr: Spec:

253.13 .999 .09424

One and a half months later, the fault has progressed to a major failure. Themonitoring schedule should be adjusted because of the speed. The spectrum showsimpacting at half harmonics indicating severe looseness. The non-synchronouspeaks are severe bearing defects.

ConclusionPeakVue worked well at detecting this high speed bearing failure. The monitoringschedule may need to be adjusted as speed increases. Even small faults canprogress to catastrophic at high speeds.



Case History - Slow Speed Gearbox

Gearbox(half)

280 HP1190 RPMAC Motor

This gearbox is used in a mining operation to remove material underground. Itpowers two large boring heads at a very slow speed. Normal vibration monitoringwas not very effective at monitoring the gears inside. The complexity of thespectrum made it difficult to determine when and where the problems occurred.



WAVEFORM DISPLAY 30-JAN-97 11:25 RMS = .0417 PK(+) = .1191 PK(-) = .1304 CRESTF= 3.13

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

-2.5-2.0-1.5-1.0-0.5

00.51.01.52.0

Time in Seconds

Acc

eler

atio

n in

G-s

CF ALARM CF ALARM

PK ALARM

PK ALARM

K1UG - # 20 Miner Normal#20 NORMAL-R9 Right Side Point 9

ROUTE SPECTRUM 30-JAN-97 11:25 OVRALL= .0477 V-DG PK = .0475 LOAD = 100.0 RPM = 1190. RPS = 19.83

0 3 6 9 12 15 18 21 24 27

0

0.01

0.02

0.03

0.04

0.05

Frequency in Hz

PK V

eloc

ity in

In/S

ec

Freq: Ordr: Spec:

9.853 .497 .02015

17 T 63 T

14 T

40 T

15 T

43 T

OUTPUTSHAFT 16.4 RPM

41 T

17 T

31 T

1 2 3

4

5

1 = 20 Hz2 = 5.393 = 1.894 = .665 = .276 = .36

Normal processing shows two peaks related to a chain drive.

PeakVue Processing



K1UG - # 20 Miner Peak Vue#20 PV -L10 Left Side Point 10

Label: OUTPUT, IDLER,

Analyze Spectrum 30-JAN-97 12:56 (Filtr-HP 1000 Hz)

RMS = .3106 LOAD = 100.0 RPM = 1200. RPS = 19.99

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

0

0.02

0.04

0.06

0.08

0.10

0.12

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

.66 1.

32

1.98

2.64

3.29

3.95

4.61 5.

27

Freq: Ordr: Spec:

.656 .03282 .06006

>MIN MINER #20 V=Grmesh(4>6) : 11.20 W=Tth Rept(4>6) : .0212 X=Speed #6 : .36 Y=Gm(4>6)-Sp4 : 11.86 A=Gm(4>6)-Sp6 : 11.56

K1UG - # 20 Miner Peak Vue#20 PV -L10 Left Side Point 10

Label: OUTPUT, IDLER,

Analyze Spectrum 30-JAN-97 12:56 (Filtr-HP 1000 Hz)

RMS = .3082 LOAD = 100.0 RPM = 1200. RPS = 19.99

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

0

0.02

0.04

0.06

0.08

0.10

0.12

Frequency in Hz

RM

S A

ccel

erat

ion

in G

-s

.36

.72

1.08

1.44

1.81 2.

17

2.53

2.89

3.25

3.61

3.97

4.33

4.69

Freq: Ordr: Spec:

.362 .01813 .06396

>MIN MINER #20 V=Grmesh(4>6) : 11.20 W=Tth Rept(4>6) : .0212

W

X=Speed #6 : .36

X

Y=Gm(4>6)-Sp4 : 11.86 A=Gm(4>6)-Sp6 : 11.56

Harmonics of the #4 shaft are apparent. The #6 shaft harmonics is also visible.

The gearbox continued to run, for a while. The picture below shows the resultswhen the failure occurred.



Conclusion



PeakVue is outstanding for slow speed and complex gearboxes. The filtering canget rid of the high amplitude GMF, and allow us to see the impacting of shafts,gear teeth and bearings.

© Copyright 1997, Computational Systems Incorporated. All rights reserved. B-1

Doctor Know™ Application PaperTitle: An Improved Methodology for Defect Detection in Gear BoxesSource/Author: J.C. RobinsonProduct: MasterTrendTechnology: PDM

ABSTRACT

A microprocessor based instrument has been developed to enhance the analysis of complexmechanical devices such as gear boxes for defect detection employing vibration analysistechniques. The physical phenomena relied on for analysis are the stress waves which are emittedas a result of metal-to-metal impacting, microwelding, etc. For rotating equipment, these stresswaves are generally emitted at a periodic rate; therefore, synchronous averaging can be employedfor signal enhancement. The pulses used for timing pulses from which synchronous averagingoccurs are generated digitally within the microprocessor based instrument. The digitallygenerated output pulse string is analytically generated from a reference input pulse stringacquired from the mechanical device under analysis.

The methodology implemented in the new microprocessor based instrument described herein wasapplied to a small double reduction gear box with a known defective tooth. The results obtainedfrom synchronous averaging of the stress waves are compared to synchronous averaging of thevibration signals (standard methodology). The results obtained using the stress wave analysiswere more informative and simpler to interpret

1.0 BACKGROUND

An accelerometer measures the absolute motion (acceleration) of the surface it is attached to.Surface motion can occur because of 1) motion of the entire body in a global sense, 2) structuralresonances of the body, and 3) stress waves traveling through the body. Entire body motion isgenerally in the lower frequency range and directly proportional to the driving force. Structuralresonances are dependent on the makeup of the body and can significantly amplify motion atspecific (resonant) frequencies. Stress waves are generally set up in a body due to localizedeffects such as impacting, microwelding (tearing), etc. For metallic objects impacting on ametallic surface, the stress waves emitted consist of bending and shear waves. As bending wavestravel away from the initiation point, they cause a small surface motion much like the pressurewaves seen in a pool of water. Shear waves, which travel faster than bending waves do notintroduce surface distortions, but do get converted to bending waves when traveling throughinterfaces. For metal-to-metal impacting, the dominant frequency in bending waves will be in the1KHz to 15 kHz range; however, the impact signature will excite a broad band of frequencies.The bending waves will attenuate as they travel away from the point of impact, but the higherfrequencies will attenuate more rapidly than the lower frequencies (approximately inversely proportional to frequency). Furthermore, the frequency content within the impact is dependent onthe impact itself, e.g., small objects or sharp surface impacting will have higher frequencies thanlarger objects or smooth surface impacting.

The large variability in frequency content due to the shape and size of the impacting object and

PeakVue TrainingAppendix B

B-2 © Copyright 1997, Computational Systems Incorporated. All rights reserved.

attenuation due to dispersion within an impacting signature makes a specific frequency difficultto impossible to monitor. The frequencies within impact signatures are generally greater thanthose within bulk vibration or larger structural resonances and hence can be separated andmonitored from a timing and energy perspective. Impacts occurring at the moving shaft (gearteeth, inner race on bearings, etc) will generate stress waves which must travel through interfaceswhere significant attenuation could occur and hence may require signal enhancement (such astime synchronization) to provide a reliable monitoring technique.

The methodology developed by CSI Patent pending. for stress wave monitoring with timesynchronous averaging capability has been implemented in a microprocessor based instrumentand is described below.

2.0 ANALYSIS PROCEDURE

2.1 IntroductionThe methodology employed achieves signal enhancement through synchronous averaging. Thesignal to be averaged is transported to the sensor as stress waves. The signal that is averaged isspecially processed to filter out low frequency mechanical contributions and then peak-hold toinsure that short duration impacts do not go undetected. The method used to generate thesynchronous pulse as well as the signal to be synchronously averaged is discussed briefly below.

2.2 Generation of Synchronous PulsesThe input for the digitally generated pulse is a once per rev pulse from an accessible (reference)shaft. The speed of the output object (shaft, bearing, etc.) must be deterministic relative to thereference shaft. A microprocessor is used to generate the output tach signal. The output pulsestring can be a higher or lower rate than the input pulse rate. The user can enter a decimatednumber or two integers where the ratio determines the output pulse string rate. A level ofintelligence has been built into the processor wherein it predicts the time of an incoming pulse. Ifthe pulse is not within a reasonable time of the expected time, it assumes that pulse is missing (orfalse) and continues the output pulse string based on historic data. This permits an occasionaldropout or an occasional false trigger from the incoming pulse string. Many false inputs (ormisses) will cause the output pulse string to be terminated. These features are very important toinsure that the subsequent synchronous averaging process is not compromised.

2.3 Signal ProcessingThe signals to be processed are the stress waves setup in metal due to impacting, micro welding,etc. The primary characteristics of these signals are that they will be of low amplitude, shortduration (5 to 100 msec), and have carrier frequencies in excess of a kilohertz. The signal fromthe sensor (an accelerometer) will be routed through a high pass filter, amplified, and thenprocessed. The information is obtained from the presence of the stress wave and its energycontent; the frequency of the carrier is of less importance. The stress waves typically travelthrough a tortuous route prior to reaching the sensor and hence will generally be small.Therefore, signal enhancement such as synchronous averaging is frequently necessary to makethe defect events detectable.

The basic signal from stress waves (impacts, etc.) general1y cannot be synchronous averaged



because a) the frequency within the packet varies somewhat due to the nature of the stressproducing source and b) the reasonably high frequency of a few kilohertz would requireunrealistic stability in the synchronous timing pulse. The envelope of the stress packet could besynchronously averaged but would require a sampling rate in the kilohertz range to assuredetection of the peak (detect the energy within the packet). The methodology adopted herein is toemploy a peak detector which can be reset at a predetermined rate. This ensures the detection ofthe peak at reasonable slow sampling rates. The basic technique is to hold the signal from inputto output such that the output in the interval t to t + _t is the maximum of the input signal fromthe previous time (t-_t) to t

To illustrate the functionality gained from this approach, consider monitoring a bearing on a shaftturning at 1 RPM. The fault frequency would be in the 5 to 25 RPM range. Early bearing defectswill generate stress waves (impacts) with time durations in the 5-50 msec range whose peakvalue could be very short lived. To look for bearing faults, one would like to capture a timerecord consisting of two or more shaft revolutions. Most portable meters have a minimum(analysis bandwidth) frequency range for the spectral analysis of (FMAX) 10 Hz which means theminimum sampling frequency is 25.6 samples/sec. For an FMAX of 10 Hz (sampling frequency of25.6), and a specified block size of 400 frequency lines, the sampled block of 1024 data pointswould take 40 sec to fill (specified 1600 frequency lines would take 160 sec to fill). A samplingrate of 25.6 sec means that one sample occurs approximately every 39 msec. If one were usingenvelope detection, the event would be entirely missed many times and synchronous averagingwould be of very little value. Using the peak hold methodology, a hold time of greater than 40msec would guarantee the peak would always be detected. This ability to correlate the peak holdtime with sampling rate permits the use of synchronous averaging for stress packet analysis onvery slow to fast machinery. Accordingly, one can carry out synchronous averaging for stresswave analysis on a wide spectrum of machinery using time synchronous averaging.

3.0 Application to a Gear Box

3.1 IntroductionThe gear box chosen for demonstration is a reduction gear box having one internal shaft. Thegear box is driven by a 1 horsepower DC motor. The load is relatively light. The input shaft has a16 tooth pinion driving a 88 tooth gearwheel on the intermediate shaft. The intermediate shafthas a 17 tooth pinion driving a 54 tooth gear wheel on the output shaft. The total speed reductionfrom input to output is:

(16/88)(17/54) = 17/297

It was known that there was a cracked tooth on one of the gears.

The sensor used for analysis was an accelerometer mounted over the bearing on the input shaft.The tach signal used for reference was from the slow output shaft. The results presented beloware:

1. No synchronous averaging.2. Synchronous for each shaft of the straight vibration signal.



3. Synchronous for each shaft for the stress wave using the peak follower methodology.

The last subsection will be a summary of the findings from the results.

3.2 Results

3.2.1 No Synchronous AveragingThe spectra for a four block average. Four blocks were chosen because this is typical fornonsynchronous averaging. With the time trace for one block of data for an analysis bandwidthof 800 Hz with 800 lines frequency analysis are presented in Figure 1. In Figure 1, there are noclear indicators that at least one gear has a defective tooth.

3.2.2 Synchronous Averaging of Vibration SignalThe synchronization on each shaft was accomplished by digitally generating a tach pulse fromthe output (slow) shaft reference tach. The multiplication factors used were as follows:

1. 1.0 for synch to output shaft.

2. 54/17 for synch to intermediate shaft.

3. 17.471 for synch to input shaft.The results obtained for a 25 block average (time and spectra) are presented in Figure 2 throughFigure 4. Examination of the time trace suggests there may be a problem on the input pinion (it isnot a clear conclusion).

3.2.3 Synchronous Averaging of Stress WaveFor this analysis, the output signal from the accelerometer was preprocessed through the systemdeveloped for peak following of the stress wave signal and then routed through an analyzer (theCSI Model 2120 was used but any similar device would be appropriate).

Results obtained by synchronous averaging 25 blocks in the data collector are presented in Figure5 through Figure 7 (the input to the data collector was the output of the microprocessor basedstress wave signal conditioner). The stress wave signal conditioner was set up as:

1. High pass set point: 500 Hz and a delay time of 5 msec.

2. Multiplication factors for input tach pulse (from gear box output shaft) were:

1.0 forFigures54/17 forFigure617.471 forFigure7



Accordingly, the synchronous results for Figure 5 are relative to the outlet or slow shaft, thesynchronous results for Figure 6 are relative to the intermediate shaft, and the synchronousresults for Figure 7 are relative to input (or fast) shaft.

From the results presented in Figures 5 through 7 it is obvious that a stress wave (probableimpact) is occurring once per revolution of the input shaft (Figure 7). There also are stress waveactivity occurring 11 times per revolutions of the intermediate shaft (Figure 6). There is nodiscernable stress wave activity associated with the output (or slow) shaft (Figure 5).

The probable causes of the observed stress wave activities are:

1. One tooth on the input shaft pinion is damaged (probably cracked).

2. The one defective tooth on the drive pinion has damaged 11 teeth on the 88 gear wheeland some impacting is occurring when the mating pinion engages any of these 11 teeth. Thecombination of 16 teeth driving 88 teeth (prime number of 2 and 11) ensures that any specifictooth on the pinion will engage only 11 of the 88 teeth on the gear wheel.

3.3 Summary of Results from Test Gear BoxFrom the results presented from an accelerometer and a tachometer used on the test gear box, itcan be concluded:

1. The microprocessor generated tachometer presents a reliable pulse string from whichsignal enhancement employing synchronous averaging can be successfully employed forboth the vibration component and the stress wave component of the signal obtained froman accelerometer.

2. The peak following circuitry employed for synchronous averaging of the stress wavecomponent functioned very well.

4.0 Conclusions

The use of a microprocessor to generate an output pulse string at a deterministic rate relative toan input reference pulse string proved very useful to permit signal enhancement throughsynchronization. Synchronous averaging was made possible for both the normal vibrationcomponent as well as the stress wave component of signals acquired by using an accelerometeras the sensor. The methodology employed here for processing the signal representing stresswaves was:

1 High pass the signal to remove the normal vibration component.

2. Holding and output the peak value over a specified time range.

3. Synchronously averaging this specially conditioned signal.



This monitoring of the peak value is capable of providing the similar information at a relativelyslow sampling rate that envelope detection would at a relatively high sampling rate. The use ofthe relatively slow sampling rate makes possible the use of the typical data collector to collectlong duration data records with the assurance of capturing short lived impulse (stress wave)events.

In addition to the ability to execute synchronous averaging of the vibration signal and the stresswave signal to inaccessible shafts in a gearbox which was demonstrated in this paper; themethodology presented here would be equally applicable to hard to detect bearing failures suchas inner race defects in the presence of high background vibration. The ability to synchronize onspecific fault event rates and the peak follower capability should prove very useful in monitoringbearings in slow machinery, gear boxes, etc.

Figure 1.Spectra and time trace from a 4 block average for an Fmax of 800 Hz and 800 line spectra.

Figure 2.Twenty five block synchronous average of vibration signal relative to output (slow) shaft.

Figure 3.Twenty five block synchronous average of vibration signal relative to intermediate shaft.

Figure 4.Twenty five block synchronous average of vibration signal relative to input shaft.

Figure 5.Twehty five block synchronous average of stress wave signal relative to output shaft.

Figure 6.Twenty five block synchronous average of stress wave signal relative to intermediate shaft.

Figure 7.Twenty five block synchronous average of stress wave signal relative input shaft.

Peak Vue

Documents

Transcript of Peak Vue