Time Waveform Analysis

(1)

TIME AND FREQUENCY ANALYSIS

Machinery vibration analysis techniques

Time domain analysis

Frequency analysis

Demodulation

TIME DOMAIN ANALYSIS

Use of time domain analysis

Signal processing and presentation

Phase measurement

Instrument setup

Time waveform shape analysis

Synchronous vs nonsynchronous data

Random noise and vibration

Conclusions

USE OF TIME DOMAIN ANALYSIS

A graphic description of the overall physical behavior of a vibration structure as a function of time

Clarification of FFT processed data

The position of the measurement point at each instant of time relative to the position at rest

Overall peak amplitude

Phase and amplitude relationships of different frequencies and different positions

The nature of amplitude modulation or frequency content

USE OF TIME DOMAIN ANALYSIS

(cont.)

The symmetry of a signal; this relates to the

linearity of the vibrating system, the nature of the

forcing function, and the severity of the vibration

A measure of damping in the system

Direction of the initial exciting force

SIGNAL PROCESSING and

PRESENTATION

Instrumentation

Presentation

Presentation setup

Differential time

Waveform Characteristics

Objectives

• Describe five waveform characteristics. • Identify waveform symmetry using APD.

• Discuss waveform modulation and how it translates to the FFT.

(2)

Waveform Characteristics

12-1 • A number of different displays "averaging modes" use the time

domain. Displays such as synchronous time averageddata is

averaged in the time domain.

• APD (Amplitude Problability Distribution) this is a function of Wavepak, displays the symmetry and skewness of the waveform signal.

• Each defect type has a characteristic waveform, which subsequently translates to the frequency domain.

• There are characteristics and specific events that do not

translate to the frequency domain as discrete peaks. In order to truly understand this limitation, the analyst must first understand how the time domain data is gathered and transformed into a spectrum through the Fast Fourier Transform (FFT) process.

Waveform Characteristics

12-2 • Time domain data, raw transducer output, signal voltage and many other terms refer to waveforms.

• Waveform or time domain data is comprised of amplitude with

respect to time. Signals with an amplitude, whether vibration, current, voltage changes, or other signal types, change with time.

Waveform Characteristics

12-2 There are certain things to look for when conducting waveform analysis, the waveform provides specific characteristics for defects of a single or multiple nature.

BAL - C-20 FLOAT ROLL FAN C-20 FLOAT-FIH FAN BEARING INBOARD HORIZONTAL

Waveform Display 25-APR-96 09:36 RMS = 1.28 LOAD = 100.0 RPM = 3550. RPS = 59.17 PK(+) = 6.94 PK(-) = 5.84 CRESTF= 5.40 0 20 40 60 80 100 120 140 -8 -6 -4 -2 0 2 4 6 8 Time in mSecs A cc el er at io n in G -s Time: Ampl: 135.09 .00000

Waveform Characteristics

12-3

Note: The waveform is only as good as its definition. If the resolution of your waveform lacks definition, the data can be worthless, or poor at best.

• Once the characteristics have been properly identified, the analyst can rule out certain fault types.

•For example:

• If a waveform is periodic (sinusoidal) • looseness

• cracks • resonance • antifriction bearings

Could probably be ruled out. You may not know what the problem is, but you know what it is not.

Waveform Characteristics

12-3 Listed below are waveform characteristics an analyst should look for when analyzing the waveform:

• Amplitude • Asymmetry • Electrical vs Mechanical • Distortions • Periodic • Spikes/Impacts • Non-Periodic • Modulation • Complexity • Discontinuities • Low Frequency Events • Truncation/Restrictions to Motion

Amplitude

12-4

• When diagnosing machinery faults using the time waveform, similar to spectral data, we are concerned with the amplitude of the waveform.

• When we are discussing bearing and gear waveforms, we use the peak to peak amplitude of the waveform. This is often referred to as g swing.

• The g swing is the sum of the absolute value of the maximum positive and negative amplitude in that period. • MasterTrend calculates this value and gives us the ability to trend and alarm based on this and other waveform values.

(3)

Amplitude

C-20 - C-20 FLOAT ROLL FAN C-20 FLOAT-FIH FAN BEARING INBOARD HORIZONTAL

Waveform Display 25-APR-96 09:36 RMS = 1.28 LOAD = 100.0 RPM = 3550. RPS = 59.17 PK(+) = 6.94 PK(-) = 5.84 CRESTF= 5.40 0 20 40 60 80 100 120 140 -8 -6 -4 -2 0 2 4 6 8 Time in mSecs A cc el er at io n in G -s ALERT ALERT FAULT FAULT Time: Ampl: 76.72 -.109 12-4

Periodic

12-5

• Sometimes referred to as a deterministic simple signal, this is an ideal signal which repeats itself exactly after a fixed period.

• This is not possible in the real world. However, there are some machinery faults which have this characteristic.

• A single plane balance problem will have a very periodic waveform due to the mass rotational center and the rotor shaft of other component center line differences.

Periodic

12-5

BAL - ZONE 6 EXHAUST C-30 Z6X -FOH FAN BEARING OUTBOARD HORIZONTAL

Waveform Display 13-JUN-95 14:52 RMS = .1390 LOAD = 100.0 RPM = 1000. RPS = 16.67 PK(+) = .3672 PK(-) = .4322 CRESTF= 3.11 0 100 200 300 400 500 -0.6 -0.4 -0.2 -0.0 0.2 0.4 0.6 Time in mSecs A cc el er at io n in G -s

Complexity

12-6

• To determine the complexity of the waveform, establish whether the signal is:

• periodic in nature

• estimate the harmonic content • determine if the signal is synchronous • non-synchronous

• identify whether the waveform correlates directly to the spectral data.

Complexity

12-6

C-20 - C-20 FLOAT ROLL FAN C-20 FLOAT-FOH FAN BEARING OUTBOARD HORIZONTAL

Label: LOOSE, OUT OF BALANCE

Waveform Display 25-APR-96 09:37 RMS = 1.59 LOAD = 100.0 RPM = 3508. RPS = 58.47 PK(+) = 4.88 PK(-) = 5.25 CRESTF= 3.30 0 20 40 60 80 100 120 140 -6 -4 -2 0 2 4 6 Time in mSecs A cc el er at io n in G -s

Impacts/Spikes

12-7 • Impacts or Spikes may or may not be repetitive in nature. • The non repetitive spikes generate white noise.

• Repetitive impacts or spikes, such as those produced by rolling element bearing defects or broken gear teeth, may excite discrete frequencies and therefore show up well in the spectrum. • This characteristic is best detected by defining a waveform amplitude type in acceleration. Acceleration data is proportional to force.

• The crest factor, which is equal to the maximum peak (positive or negative) divided by the RMS of the waveform, is a good indicator of the impacting. This value can be setup as an analysis parameter and trended in MasterTrend.

(4)

Impacts/Spikes

12-7

Repetitive Spikes

Discontinuities

12-8

• This characteristic is usually associated with faulty equipment due to the discontinuous nature of the data.

• Data with this characteristic has breaks in the data where there appears to be a loss of input signal or a significant increase/decrease in amplitude.

• This is not a uniform change such as resonance, load changes, or even sudden component failures. • Discontinuous data is typically unpredictable, and very distinct.

• If you see this type of waveform pattern ( YOU HAVE A PROBLEM )

Discontinuities

12-8

Asymmetry

12-9

• Asymmetry refers to the relationship between the positive and negative energy.

• A waveform is asymmetricwhen there is more energy in

the positive plane than the negative or vice versa.

• Asymmetry refers to the direction of movement relative to

the transducer mounting with a positivesignal

representing energy into( towards ) the accelerometer and

a negative signal representing away.

• A tool which is designed to check this type of characteristic is the APD, Amplitude Probability Distribution.

Asymmetry

12-9

MISC - #1 H2O BOOSTER 4661 -MIV MOTOR INBOARD VERTICAL

Label: LOOSE BASE

Waveform Display 16-NOV-95 10:18 RMS = .5155 LOAD = 100.0 RPM = 1789. RPS = 29.82 PK(+) = 2.24 PK(-) = 1.43 CRESTF= 4.35 0 60 120 180 240 300 -2.0 -1.5 -1.0 -0.5 0 0.5 1.0 1.5 2.0 2.5 Time in mSecs A cc el er at io n in G -s

Asymmetry

12-10 Select the Analyze Data feature in Diagnostics Plotting when in Waveform Analysis.

(5)

APD

12-10

APD

12-11 Amplitude Probability Distribution

• An APD or Amplitude Probability Distribution is similar to a Hystorgram.

• The signal is broken down into amplitude percentages, and then the amplitude is plotted.

• The X-Axis is the amplitude and the Y-Axis is the percentage of the signal that falls into that amplitude range.

• The APD is typically used for acoustical analysis. It can also be used for machine vibration analysis to find the balance of the signal (asymmetries), the direction, and possibly the location of a specific defect especially those that may not stand out in the waveform or the spectrum.

Sinewaves

• Sinewaves are very symmetrical, which means there is a balance of energy in the positive and negative planes.

• If most of the vibration signal is evenly distributed and sinusoidal, there is a strong possibility it is due to a synchronous component such as imbalance, misalignment, gears, blades, etc.

• The waveform and APD show the shape of a sinewave and the probability related to this type of signal.

12-11

Sinewaves

12-11

• Notice that the APD at the bottom of the above display shows a set of peaks at the maximum and minimum amplitude locations. • This could also be called a Hysteresis display. The probability of the signal being in the ± 10 volt location is much more probable that the signal being at the zero location of the display.

Triangle Wave

12-13

• With a triangle wave, we see the relationship of the waveform and a different type of APD display. • Note that the data is skewed to the negative plane. Again, this provides the analyst with the direction of motion.

The following illustration displays the direct relationship between the waveform and the APD. Bear in mind that the APD provides another tool to determine location, direction, and asymmetry.

Triangle Wave

(6)

Squarewave

12-14

• The squarewave on the next slide provides some insight into the use of the APD for checking asymmetries. Remember that symmetry refers to the balance of energy. Therefore, with a slightly more complex signal, this becomes more important especially when performing Root Cause Failure Analysis(RCFA).

• In the next illustration, the signal is asymmetric, and there

is more energy in the positive plane than the negative. • The energy in the positive plane shows movement toward the transducer, and the negative plane is obviously the opposite.

Squarewave

12-14

Truncation/Restrictions to Motion

12-15 • Truncationmeans to abruptly shorten, or to appear to terminate.

• In waveform analysis, this characteristic indicates restrictive motion.

Modulation

12-15

• All the waveform characteristics up to this point have dealt with signals of a constant amplitude.

• A varying signal will cause the waveform to become modulated. The type of modulation occurring determines its classification. Commonly referred to as Beat frequencies, these may be broken into three specific categories. • Amplitude • Beating • Frequency

Amplitude

12-16

• The spectrum will have a peak at the signal's frequency with one peak on each side spaced at the frequency of the amplitude change. These peaks are referred to as sidebands.

• Amplitude modulation is common when analyzing inner race bearing defects. This occurs when the defective bearing component passes in and out of the bearing load zone. The middle of the load zone is typically where the highest amplitudes in the waveform show up.

Amplitude

12-16

•The spectrum and waveform show slot pass frequency from an AC induction motor. The primary signal at 34xTS is marked with a vertical line. The sideband cursors mark the amplitude change at 120 Hz.

(7)

Beating

12-17

• A beat is comprised of two unrelated single frequency signals, closely spaced in frequency. • Beating is often found in two pole induction AC motors. The close proximity of two times line frequency and the second harmonic of turning speed cause this beat.

• An example of beating is shown next. The 2x RPM and 2x line frequency are separated by less than .5 Hz. The waveform shows the amplitude modulation associated with beating.

Beating

12-17 WAVEFORM DISPLAY 06-DEC-94 10:15 RMS = .0678 PK(+) = .1300 PK(-) = .1790 CRESTF= 2.64 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 -0.20 -0.15 -0.10 -0.05 -0.00 0.05 0.10 Time in Seconds A cc el er at io n in G -s

AMGL - CENTAC 3 STAGE COMPRESSOR #1 CENTAC -1BA MOTOR OUTBD AXIAL TO 200 Hz

REFERENCE SPECTRUM 06-DEC-94 10:15 OVRALL= .0581 V-DG PK = .0380 LOAD = 100.0 RPM = 3575. RPS = 59.58 60 80 100 120 140 160 180 0 0.01 0.02 0.03 0.04 Frequency in Hz P K V el in In /S ec Freq: Ordr: Spec: Dfrq: 119.00 1.997 .02520 1.000

Frequency

12-18

• Rarely seen in a routine environment, this is a change in frequency without a change in the signal amplitude. Frequency modulation typically occurs in gearmeshing vibration, due to the small speed fluctuations caused by tooth spacing errors and faults as they develop. A very wide spread of sidebands in the spectrum is usually an indication that significant frequency modulation is present.

• On our example shown next. The vertical line in the spectrum marks gearmesh frequency at 24xTS. The sideband cursors mark the output shaft speed with labels identifying sidebands spaced at input shaft speed. The waveform has been expanded to show the frequency modulation occurring. A good illustration is shown between 170 and 180 msecs.

Frequency

12-18

Frequency modulation

Low Frequency Events

12-19

When performing detailed analysis, you need to be able to collect and analyze data in excess of one minute for low frequency problems. This is extremely important when the machine in question has an operational speed below 200 RPM. The challenge in identifying low frequency defects is having sufficient time in the waveform. A low frequency event may only appear once in the collected time domain. As discussed earlier, this event will not be transformed into the spectrum.

Low Frequency Events

(8)

Electrical vs. Mechanical

12-20

• Determining if the source of energy is mechanical or electrical is sometimes difficult.

• Appropriately set up waveforms can be a great help. Setting up for a long enough time to capture the operational conditions and the machine shutoff point can identify the source.

• The advantage of using the time domain as opposed to the frequency domain is there is no need to worry about the screen update time or sampling rate.

Electrical vs. Mechanical

12-20

Waveform and Spectrum

Relationships

12-21

• Each spectrum has an associated waveform. The spectrum is made of this waveform. As discussed earlier in this section, some of the characteristics in the waveform do not translate to the FFT due to the way the calculations are made. The assumption is that there is a repetitive cycle of events made up of sines and cosines. However, this is not actually the case.

• If an event happens only once, then this event has no frequency; therefore, the spectral representation is a continuous spectrum.

• In the waveform shown next, there is no repetition in the event; therefore, there is no frequency.

Waveform and Spectrum

Relationships

12-21

Modulated Waveforms

12-22 • Finally, when modulation is involved, there is a direct relationship between the waveform and the spectrum

depending on the differential time (∆t).

• Knowledge of the modulation ∆t helps determine the

resolution required for detailed spectral analysis. Also, from our previous discussion on modulation, we know there is a carrier frequency that the modulation must follow.

Gears, bearings, and electrical defects each have carrier frequencies. For gears the carrier is the frequency where the gears mesh. However, a carrier frequency for an electrical defect could be the line

frequency (FL) or 2 * FL.

Modulated Waveforms

(9)

Waveform Analysis As Confirmation

12-23 • Every fault condition has a corresponding waveform characteristic.

• Unbalance, for example, has a sinusoidal pattern with one major event per revolution.

•Misalignment, which is primarily offset, typically has harmonic activity with the waveform having the same number of events per cycle as the spectral data has peaks. A misalignment condition generating a second and possibly a third order peak shows two or three sinewaves per revolution.

• Loosenesswill have a complex waveform with many peaks within one revolution. This will confirm the spectral characteristics of multiple harmonics of turning speed.

Vertical Turbine Pump

Unbalance Example

12-24 MOH MIH MOV MIV

Vertical Turbine Pump

Unbalance Example

• The multiple point spectrum plot below shows radial and axial measurements taken from the top of the vertical motor.

FWEL - FRESH WATER BOOSTER PUMP 1 131-546-03 - PTS=MOH MOV MOA

P K V el oc ity in In /S ec Frequency in Order 0 3 6 9 12 15 18 21 24 27 Max Amp .65 Plot Scale 0 0.7 09-FEB-96 09:22 131-546-03-MOH 09-FEB-96 09:22 131-546-03-MOV 09-FEB-96 09:22 131-546-03-MOA 12-25 M ul ti-sp ec tra l -D at a C om pa ris on

Vertical Turbine Pump

Unbalance Example

12-26 • The sharpness of the peak indicates that it has been created from a waveform dominated by a single frequency.

FWEL - FRESH WATER BOOSTER PUMP 1 131-546-03-MOV MOTOR OUTBOARD VERTICAL

Route Spectrum 09-FEB-96 09:22 OVRALL= .6466 V-DG PK = .6464 LOAD = 100.0 RPM = 1776. RPS = 29.60 0 5 10 15 20 25 30 35 40 45 50 0 0.2 0.4 0.6 0.8 1.0 Frequency in Order Ordr: Freq: Spec: 1.000 1776.2 .646 S in gl e S pe ct ru m -A m pl itu de R el at io ns

Vertical Turbine Pump

Unbalance Example

12-27 • Approximately 270 milliseconds of time (8 shaft revolutions) shows the clear one per revolution signal generated by the

unbalance condition. FWEL - FRESH WATER BOOSTER PUMP 1

131-546-03-MOV MOTOR OUTBOARD VERTICAL Waveform Display 09-FEB-96 09:22 RMS = .2679 LOAD = 100.0 RPM = 1776. RPS = 29.60 PK(+) = .5932 PK(-) = .6215 CRESTF= 2.32 0 60 120 180 240 300 -0.8 -0.6 -0.4 -0.2 -0.0 0.2 0.4 0.6 0.8 Time in mSecs A cc el er at io n in G -s Ti m e W av ef or m -S in us oi da l

Fan Bearing

Looseness Example

12-28 The fan bearing looseness data provides the initial spectral data for diagnostics and the waveform data to confirm the looseness fault diagnosis.

The fan ran in an out of balance condition for two years. The bearings now have excess clearance, allowing the shaft to move

around.

(10)

Fan Bearing

Looseness Example

12-29 Note the small amounts of harmonic activity and axial data

amplitude. C-20 - C-20 FLOAT ROLL FAN

C-20 FLOAT - PTS=FIH FIV FIA FOH FOV FOA

P K V el oc ity in In /S ec Frequency in Order 0 2 4 6 8 10 12 14 16 Max Amp .46 Plot Scale 0 1.0 14-JUN-95 08:08 C-20 FLOAT-FIH 14-JUN-95 08:09 C-20 FLOAT-FIV 14-JUN-95 08:09 C-20 FLOAT-FIA 14-JUN-95 08:09 C-20 FLOAT-FOH 14-JUN-95 08:10 C-20 FLOAT-FOV 14-JUN-95 08:10 C-20 FLOAT-FOA Ordr: Freq: Sp 1: 1.000 3499.0 .395 M ul ti-sp ec tra l -D at a C om pa ris on

Fan Bearing

Looseness Example

12-30 The spectral plot below shows vibration in the

horizontal direction on the fan outboard bearing.

Label: HARMONICS-BALANCE/LOOSENESS Route Spectrum 14-JUN-95 08:08 OVRALL= .5095 V-DG PK = .5065 LOAD = 100.0 RPM = 3498. RPS = 58.30 0 2 4 6 8 10 12 14 16 0 0.1 0.2 0.3 0.4 0.5 0.6 Frequency in Order P K V el oc ity in In /S ec Ordr: Freq: Spec: 1.000 3499.0 .395 S in gl e S pe ct ru m -A m pl itu de R el at io ns

Fan Bearing

Looseness Example

12-30

• The cursor markers note the locations of harmonics of running speed.

• Virtually all the vibration energy in this spectrum is caused by turning speed and harmonics. The sides, or skirts, of this peak are also very narrow.

• The number of harmonics tells us that the spectrum is derived from a complex, repetitive time waveform.

Fan Bearing

Looseness Example

12-31

Label: HARMONICS-BALANCE/LOOSENESS Waveform Display 14-JUN-95 08:08 RMS = 1.06 LOAD = 100.0 RPM = 3498. RPS = 58.30 PK(+) = 3.08 PK(-) = 3.01 CRESTF= 2.88 0 30 60 90 120 150 180 210 240 -4 -3 -2 -1 0 1 2 3 4 Time in mSecs A cc el er at io n in G -s Ti m e W av ef or m -S in us oi da l C ha ra ct er

Fan Bearing

Looseness Example

12-31

• A clear and repeatable waveform occurs once per shaft revolution, 1 x RPM.

• There is also multiple peaks within one revolution The waveform shows the acceleration created on the bearing housing by the looseness.

• The repeatability of the waveform in time with respect to the shaft turning speed and amplitude means that the vibration force is tied to the shaft running speed.

Motor to Pump

Misalignment Example

12-32 The pump has had high vibration since installation and

numerous seal/packing and bearing failures. The maintenance personnel stated that the alignment was “difficult” because the base was drilled incorrectly at the manufacturers facility.

M1H M1V M1A M2H M2V P1H P1V P2H P2V P2A P1A M2A

(11)

Motor to Pump

Misalignment Example

12-33 At first glance, the problem might appear to be unbalance. If we take a closer look we see that 2X running speed peaks

are present in all directions. #1 - TIMBERLINE BOOSTER (PROSPECT

TIMBSTRPRO - PTS=MOH MOV MIH MIV MIA

P K V el oc ity in In /S ec Frequency in Order 0 5 10 15 20 25 30 35 40 45 50 55 Max Amp .43 Plot Scale 0 0.5 21-JUN-95 16:11 TIMBSTRPRO-MOH 21-JUN-95 16:11 TIMBSTRPRO-MOV 21-JUN-95 16:11 TIMBSTRPRO-MIH 21-JUN-95 16:11 TIMBSTRPRO-MIV 21-JUN-95 16:12 TIMBSTRPRO-MIA M ul ti-S pe ct ra l -A m pl itu de C om pa ris on

Motor to Pump

Misalignment Example

12-34 • Harmonics of running speed are denoted by the fault

frequency markers (dashed lines).

• The first through sixth orders of running speed are visible

with the 2X T.S. predominant. #1 - TIMBERLINE BOOSTER (PROSPECT

TIMBSTRPRO-MIV MOTOR INBOARD VERTICAL Reference Spectrum 21-JUN-95 16:11 OVRALL= .1780 V-DG PK = .1771 LOAD = 100.0 RPM = 1768. RPS = 29.47 0 3 6 9 12 15 18 21 24 27 0 0.03 0.06 0.09 0.12 0.15 0.18 0.21 0.24 Frequency in Order P K V el o ci ty in In /S ec Ordr: Freq: Spec: 1.004 1774.9 .01562 A=MOTOR HARMONIC : 1.00 A A A A A S in gl e S pe ct ru m -2x TS

Motor to Pump

Misalignment Example

12-35 The waveform is repetitive for each revolution with two distinct

peaks for each period. #1 - TIMBERLINE BOOSTER (PROSPECT

TIMBSTRPRO-MIV MOTOR INBOARD VERTICAL

Waveform Display 21-JUN-95 16:11 RMS = .1784 LOAD = 100.0 RPM = 1768. RPS = 29.47 PK(+) = .5682 PK(-) = .5457 CRESTF= 3.19 0 60 120 180 240 300 -0.8 -0.6 -0.4 -0.2 -0.0 0.2 0.4 0.6 0.8 Time in mSecs A cc el er at io n in G -s 1 2 Ti m e W av ef or m -Tw ic e pe r R ev ol ut io n

Pump Bearing

Looseness Example

12-36 • The diagram above shows a centerhung pump with bearing housing dimensions worn oversize .

• The worn housings makes the pump very loose .

• Typical of many looseness problems, this has grown worse over time. A small dimension problem has gradually made itself worse.

Speed 1775 RPM

H.p. 150

Pump Bearing

Looseness Example

12-37 Many harmonics of running speed are visible on all measurement positions. Baseline or floor energy is also very visible.

CWTR - COOLING WATER PUMP 1 341-545-01 - PTS=PIV PIH POV POH POA

P K V el oc ity in In /S ec Frequency in Hz 0 400 800 1200 1600 Max Amp .14 Plot Scale 0 0.14 18-APR-96 08:46 341-545-01-PIV 18-APR-96 08:46 341-545-01-PIH 18-APR-96 08:46 341-545-01-POV 18-APR-96 08:47 341-545-01-POH 18-APR-96 08:47 341-545-01-POA M ul ti-sp ec tra l -B ro ad ba nd

Pump Bearing

Looseness Example

12-38

CWTR - COOLING WATER PUMP 1 341-545-01-POA PUMP OUTBOARD AXIAL

Route Spectrum 18-APR-96 08:47 OVRALL= .3663 V-DG PK = .3675 LOAD = 100.0 RPM = 1775. RPS = 29.58 0 400 800 1200 1600 0 0.02 0.04 0.06 0.08 0.10 0.12 0.14 Frequency in Hz P K V el oc ity in In /S ec Freq: Ordr: Spec: 29.58 1.000 .03901 S in gl e S pe ct ra l - 9-15 xT S a nd Bro ad ba nd

(12)

Pump Bearing

Looseness Example

12-38

• A cursor is positioned at 1x running speed and on the harmonics of running speed.

• The peaks are broad and have wide skirts.

• Notice, no individual peak exceeds .1 in/sec, but the overall energy is .3663 in/sec.

• This is common with looseness. Broad humps of energy show up in the 9X to 15x running speed range.

• This indicates that the time waveform cannot be cleanly transformed into a spectrum. Therefore, the waveform must have random, non-periodic energy present.

Pump Bearing

Looseness Example

12-39

• There is no similarity in its pattern from revolution to revolution. Non-periodic, random patterns do not convert well in the FFT process. It is very difficult to assign specific frequencies and amplitudes to patterns in waveforms like the one on the next page.

• This difficulty leads to the broadband energy humps in the spectrum. Broader humps indicate more random energy. Higher humps indicate more impacting in the waveform.

Pump Bearing

Looseness Example

12-39

CWTR - COOLING WATER PUMP 1 341-545-01-POA PUMP OUTBOARD AXIAL

Waveform Display 18-APR-96 08:47 RMS = 2.12 LOAD = 100.0 RPM = 1775. RPS = 29.58 PK(+) = 7.68 PK(-) = 6.42 CRESTF= 3.63 0 60 120 180 240 300 -8 -6 -4 -2 0 2 4 6 8 10 Time in mSecs A cc el er at io n in G -s Tim e W av ef or m -R an do m E ne rg y

Rolling Element Bearing Example

12-40 • Maintenance personnel reported vibration from the back end of the motor after only 200 hours operating time on a newly installed drive.

• The analyst investigated and found visible flakes of a bronze colored material near the back end of the motor. The motor manufacturer was contacted to determine if the 6330 bearings had a bronze retainer and the reply given was no.

Ski Lift Motor

850 HP DC Motor Right Angle Gearbox

6330 Bearings

Rolling Element Bearing Example

12-41

• All the levels appear very low in amplitude, but notice the location of the

dominant peaks.

• There appears to be groups of many peaks closely spaced in the mid to higher frequency range. These “mounds of energy” can indicate bearing

defects. NSTR - BACKSIDE QUAD

BACKSIDEQD - PTS=MOV MOA MOH

P K V el oc ity in In /S ec Frequency in Hz 0 400 800 1200 1600 2000 Max Amp .19 Plot Scale 0 0.20 05-JAN-96 08:46 BACKSIDEQD-MOV 05-JAN-96 08:57 BACKSIDEQD-MOA 05-JAN-96 08:56 BACKSIDEQD-MOH M ul ti-sp ec tra l -N on -S yn ch ro no us E ne rg y

Rolling Element Bearing Example

12-42

• The fault frequencies for the 6330 bearing ball pass frequency outer race

are marked. Notice the number of peaks surrounding the higher frequency defect harmonics.

• The large number of harmonics and sidebands will be created from a

complex waveform. NSTR - BACKSIDE QUAD

BACKSIDEQD-MOH MOTOR OUTBOARD HORIZONTAL

Label: OUTER RACE FREQUENCIES W/CAGE SB

Analyze Spectrum 05-JAN-96 08:56 PK = .3611 LOAD = 100.0 RPM = 1298. RPS = 21.64 0 400 800 1200 1600 2000 0 0.06 0.12 0.18 0.24 0.30 Frequency in Hz P K V el oc it y in In /S ec Freq: Ordr: Spec: 77.50 3.582 .03297 >SKF 6330 C=BPFO : 77.64 C C C C C C C C C C S ingl e S pe ct ru m -B ad B ea rin g

(13)

Rolling Element Bearing Example

12-43

NSTR - BACKSIDE QUAD BACKSIDEQD-MOH MOTOR OUTBOARD HORIZONTAL

Label: OUTER RACE FREQUENCIES W/CAGE SB

Waveform Display 05-JAN-96 08:56 RMS = 1.75 LOAD = 100.0 RPM = 1298. RPS = 21.64 PK(+) = 5.81 PK(-) = 5.13 CRESTF= 3.32 0 40 80 120 160 200 -6 -4 -2 0 2 4 6 8 Time in mSecs A cc el er at io n in G -s Ti m e W av ef or m -B ad B ea rin g

Rolling Element Bearing Example

12-43

The number and height of the spikes in the time

waveform confirm the presence of severe impacting.

The waveform shape is random and complex. This

shape cannot be transformed into a clean spectrum,

so the spectrum on the previous page with broad

humps of energy is created.

The bearing cage turned out to be bronze! It was

deteriorating and did not have much life left. The outer

race had major spalls from impacting balls. The

bearing was replaced.

12-44

This is an example of Unbalance.

12-44

This is an example of Unbalance.

The cursor on the previous slide is marking 1xTS

(1 Order) at 59.34 Hz in the Spectrum.

How does that frequency relate in the Waveform.

The discussions on waveform analysis are not

intended for the analyst to discard the Spectral

analysis.

The Spectrum is Amplitude vs. Frequency. The

Time Waveform is Amplitude vs. Time.

12-45

Now let us look at the Waveform in “Time”.

This is an example of Unbalance.

12-45

This is an example of Unbalance.

The cursors are marking the harmonics of

the turning speed frequency, harmonic

cursors was selected. The frequency at

59.34 Hz 0r 59.35 Hz. = (1 Order).

The time is 16.85 msec. 16.85 msec

divided by 1000 = .01685 sec, this is the Time

to complete 1 revolution.

Frequency = 1 divided by the Time

1 divided by .01685 = 59.347 Hz = turning

speed of the rotor.

(14)

This is an example of Unbalance.

12-46

• Change the display to “Revolutions”of the shaft.

• Notice the time is now 1.000 that is (1 Order).

• Viewing the Waveform in “Revolutions”can often make

analyzing a little simpler.

Misalignment Example

12-47

• Now look at a Misalignmentexample.

• The cursors are marking harmonics of turning speed. The peak at 2x turning speed is the highest amplitude. We have 3 or 4 peaks per revolution of the shaft in the Time Waveform.

Misalignment Example

12-48 • Take a closer look at the misalignment waveform pattern. • Harmonic cursors are marking the harmonics of what frequency? • From this display you still do not really know! You only know that these marked peaks are harmonic.

Misalignment Example

12-49 • From this display the same frequency was marked and the

“Set Mark”enabled, and the “Difference” cursors was selected.

Misalignment Example

Look at the time, it is 13.05 msec.

13.05 msec divided by 1000 = .01305 sec

1 divided by .01305 sec = 76.63 Hz

76.63 Hz x 60 = 4598 rpm

When we look at the freq: 76.65 in the display at

lower right hand corner we can see the frequency

has already been calculated for us. The

harmonics displayed are harmonics of 76.63 Hz.

This the frequency of 1xTS.

12-49

Misalignment Example

12-50

• Change the display to “Revolutions”of the shaft.

• Mark the same frequency, “Set Mark” select “Difference”

(15)

Misalignment Example

12-51

• We can control the cursor and look at the “ time”.

• The “ time”is in Orders .999 orders.

• We must remember it is very difficult marking exact frequencies in the Time Waveform.

Misalignment Example

12-52 • 1x turnining speed is at 76.63 Hz. 76.63 Hz x 60 = 4598 rpm. • We can see two events occurring in 1 revolution of the shaft. • How often is the second event occurring in the Time Waveform

• We will mark the 1st_event_{, select}_{“Set Mark”}_{, select}

“Difference”cursors

Misalignment Example

12-52

Move cursor to the peak representing the 2

nd

_{event in}

one revolution.

– Look at the “ time”between these two frequencies. It is

6.523 msec. 6.523 divided by 1000 = .006523 sec. – 1 divided by .006523 sec = 153.3 Hz

– 153.3 Hz x 60 = 9,196 rpm

– The 1x TS was 4,598 rpm, 4,598 x 2 = 9,196 rpm

Now, it is easy now to see that this frequency is

occurring at

2 x TS

of the rotor. It is repeated every

revolution of the shaft.

Bearing Problem

12-53

On the following slide the cursor is marking

1xTS, we have peaks at the bearing defect

frequencies.

Also displayed on the following slide is the

Spectrum with Fault Frequencies for the BPFI .

The Primary calculated defect frequency for the

BPFI is 5.91 orders. There are about 10

harmonics of 5.91 orders in the spectral data.

Bearing Problem

12-53

Bearing Problem

12-54 • How do the bearing frequencies relate in the Time Waveform? • This display shows the Fault Frequencies for the BPFI displayed.

• We must realize that the dotted lines do not automatically fall on the defect frequency we may want to mark. Just any frequency was selected. Notice where the fault lines are now.

(16)

Bearing Problem

12-55 • In the plot displayed below the cursor was placed on a different frequency before the fault lines where brought up. We can see that the fault lines will fall where we place the cursor.

Bearing Problem

Our main concern is knowing the spacing of the defect

frequencies. This is what is displayed when we bring

up the fault frequencies in the Time Waveform, the

“

Spacing”

.

Let us examine the Waveform further:

The Primary calculated defect frequency for the

BPFI = 134.4 HZ, so the repetition rate of the

impacts would calculate to 134.4 Hz.

We still have to find the impacts that are occurring at

that spacing. This will take some time for the analyst

to develop this ability to spot the equal spacing.

12-55

Bearing Problem

12-56 • When initially viewing the Waveform we look for events that are repeated, we also look for events that are equally spaced. In this plot there are several events that are repeated and equally spaced.

Bearing Problem

12-56 • We know from the Spectral display that we have an inner race

defect. Let’s display the fault frequency for the BPFI, first without

a cursor marking any event.

Bearing Problem

12-57 • All we are trying to do with this display at this point is to look for impacts that may represent the BPFI. There could be BPFO’s, BSF’s also. We will focus on the BPFI’s.

Bearing Problem

12-57 • After placing the cursor on a peak we suspect is an impact from a BPFI, then displaying the fault frequency for the BPFI, we can see we have several peaks that match up.

(17)

Bearing Problem

12-58 • We can view an expanded plot to see this a little clearer.

Bearing Problem

12-58 • Place the cursor on an impact that matches up with a fault

line. Select the “Set Mark”option. Select “Difference”

cursor. Move the cursor to the next fault line, now look at the Freq: at lower right hand corner. This should be very close to the Primary Calculated Freq. for the BPFI.

In this example it is very close.

Bearing Problem

12-59

• Alarms can also be utilized in Waveform analysis.Select Set-Up

from Tool Bar and you can set the Alarms and display them in the Waveform.

Bearing Problem

12-59

Bearing Problem

12-60

• The value for the Crest-Factor has been set to Peak 1.5 for the display seen below.

Bearing Problem

(18)

pumps, fans, steam flow, late life bearings random vibration and noise

nonsynchronous frequencies cause moving, non stationary waveform synchronous vs

nonsynchronous

truncation of signal by bearings, supports, foundations or couplings – nonlinear behavior truncated beats

bearings, gears, rolls – natural frequencies or forcing frequency modulated by low frequency that is generated by the fault

modulated pulses

motor faults, gears, bearings – a forcing frequency is modulated by a fault frequency modulated frequencies

bearings, recips, flat spots, gear teeth (broken) – some functional; some fault based pulses

grinders, motor driven fans, pumps where two forcing frequencies are close beats

generators (slot passing), gears, vane pass, bearings, naturally generated harmonics superimposed on 1x multiple harmonics

heavy 1x behavior can excite order located natural frequencies order excited natural

frequencies

misalignment, looseness, generator faults orders

rubs, oil whirl, resonance, trapped fluid hysteresis, looseness subharmonics

gear mesh, blade pass, natural frequencies, nonlinear behavior truncated harmonics

excessive mass unbalance, thermal growth, bearing clearance problems, pedestal nonlinearity, rubs truncated 1x

mass unbalance, resonance, eccentricity, misalignment, bow, blade/diffuser interaction harmonic

MECHANISM SHAPE

TABLE 4.5. TIME WAVEFORM SHAPE ANALYSIS

Part 1 - Summary

12-61 • Waveform data may be used for much more than what is typically seen in industry. The ability to check for specific characteristics such as periodicity and modulation, helps the analysis process.

• Energy balance (asymmetry) may be checked for direction of signal and for the predominant traits of the signal.

• Overall waveform is much more understandable and useful than most would lead us to believe. However, this section enhances your analysis abilities using the time waveform.

DIGITIZED TIME DOMAIN

— TRENDS

What is this spectrum Lines?

DIGITIZED TIME DOMAIN

— DETAILS

What is this spectrum Lines?

PRESENTATION OF TIME

WAVEFORM

TIME (sec.) DISPLAY PURPOSE

T/100 - - - DETAILS OF T/80 HIGHER FREQUENCY T/20 T/10 - - - -- -TRENDS OF T/3 HIGHER FREQUENCY T/2 T - - - -- - - BALANCING/PHASE 2T 3T 10 T- - - -- - - PHASE TRENDS 20T

Table 4.4. An Approach to the Presentation of a Standardized Time Waveform4.1

(19)

TIME DOMAIN WAVEFORM — SHORT

TERM

4000 HP Electric Motor with 20T Display

TIME DOMAIN WAVEFORM — BALANCING

4000 HP Electric Motor with T Display

TIME DISPLAY — SMALL MOTOR

400T

Small Motor with a 400T Display

SMALL MOTOR 100T

Small Motor with a 100T Display

(20)

PRESENTATION SETUP

Visual process

Setup to accommodate visual analysis

– to evaluate • periodicity

– to evaluate amplitude changes

Processing types

– dual processing – expansion

STANDARD SETUP

Standard Time Waveform Display from an FFT Analyzer

DUAL PROCESSING

Dual Processing to Enhance the Time Waveform

SPECTRUM: – 10x operating speed

– fmax= 250 Hz

TIME WAVEFORM: – Period = = 0.0421

– Display = 8 cycles x 0.0421 0.336 sec – Use 0.4 sec then

DUAL PROCESSING

= =

Dual Processing means:the capability to produce each Spectrum and Time waveform data independently

(spectrum Fmax not equal to waveform Fmax)

(21)

TRUNCATED HARMONIC

Clipped Vane Pass Signal from Hull of a Ship

SUBHARMONIC

Loose Bearing Housing — ½ Orders and Multiples

ORDERS

Nonlinear Generator Pedestal Response to Differing Vertical Stiffness

FAR REMOVED ORDER

Slot Passing Frequency, 36X, Generated by Air Gap Variation (120 Hz)

(22)

AMPLITUDE MODULATION

Sidebands Caused by Amplitude Modulation — Broken Rotor Bar

PULSE INDUCED NATURAL

FREQUENCIES

Pulse Induced Natural Frequencies in Printing Roll

TRUNCATED BEATS

Truncated Beat Waveform from a Motor Driven Fan

SYNCHRONOUS ORDERS

Exciter to Generator Misalignment Causing 1x and 2x

RANDOM NOISE and VIBRATION — RMS

AVERAGING

CONCLUSIONS

_{True physical behavior}

Determine origin of frequencies

Determine severity

(23)

NONSYNCHRONOUS MULTIPLE

FREQUENCIES

Boiler Feed Pump Drive — Nonsynchronous Second Order and Multiples

SINUSOIDAL AMPLITUDE

MODULATION

Amplitude Modulation by a Single Frequency

NONSINUSOIDAL AMPLITUDE

MODULATION

Amplitude Modulation in a Gearbox — Nonsinusoidal

MACHINE RESPONSE TO IMPACT

EXCITATION

Response of a Machine to Impulse Excitation

IMPACT INDUCED NATURAL

(24)

FREQUENCY MODULATION

Torsional Vibration a Form of Frequency Modulation

DIFFERENCE FREQUENCIES

Two Lobed Blower Generated Difference Frequencies — Pressure Pulsations Generated by Lobes Passing Discharge Port

MECHANISMS FOR

ORDER GENERATION

Natural excitation

Nonlinear parameters

Signal truncation

BEAT MECHANISM

Figure 4.50. Beat Mechanism

TRUNCATED BEATS

Hypothetical Vibration Response Exhibiting Beat Frequency

SUM and DIFFERENCE

FREQUENCY TABLE

(25)

SUM and DIFFERENCE

FREQUENCY MECHANISMS

Rotating Machinery Fault Diagnosis Using Sum and Difference Frequencies (Sidebands) (After Eshleman 4.2)