A Study of Rolling Element Bearing Defect Analysis

Extensive literature is available on diagnosing rolling element bearing defects using vibration analysis. However, answers to many questions remain elusive, such as the effects of rotor weight (load), speed, and damage severity on the vibration signature. SpectraQuest plans to publish a series of articles addressing these issues. This article, first in the series, will cover the effect of rotor weight, speed, and defect severity on outer race fault spectra. SpectraQuest’s Machinery Fault Simulator (MFS) provides a platform to study bearing faults. The following tests are performed on MB ER-10K bearings with lightly and moderately faulted outer race. To acquire and analyze data, VibraQuest data acquisition and analysis software, SpectraPad portable data acquisition device, and six PCB accelerometers were used.

Test Setup

Test Setup – with one loader installed The whole test setup is demonstrated in the picture above. The belt drive is not connected to prevent interference in spectrum. The faulted bearing is installed in the inboard bearing housing. Accelerometers are installed in vertical and horizontal directions on the motor and two bearing housings.

Faulted bearing

Two loaders are installed

The above picture shows the configuration with two loaders installed.

SpectraPad Portable Data Acquisition Device All the sensors are connected to the portable SpectraPad, shown above. The SpectraPad communicates with a laptop via PCMCIA.

Test Procedure

1. Mount the lightly faulted bearing in the inboard bearing housing. 2. Mount all the sensors and connect them to the SpectraPad unit. 3. Start VibraQuest software data acquisition panel, and run the MFS with 3

different rotor weights (normal configuration of 2 pound weight with 2 disks, 1 loader of 14 pounds, and 2 loaders totaling of 26 pounds) at 4 different rotating speeds (1000, 1500, 2000, and 4000 RPM). Collect the data while machine runs in a steady state condition. Data is collected for each configuration at a max frequency of 5kHz with 3,200 spectral lines and 32 blocks.

4. Repeat the above steps for moderately faulted bearing.

Test Data Analysis

The data files are analyzed using the Rotating Machinery Analysis (RMA) module in VibraQuest. MB ER-10K bearing parameters: Number of rolling elements: 8 Rolling element diameter: 0.3125 inch Pitch diameter: 1.319 inch Contact angle: 0 degree To calculate the BPFO multiplier, the following formula is used:

)cos*1(*2

θPdBdNbBPFO −=

Where, BPFO = Ball pass frequency multiplier of the outer race Nb = Number of rolling elements. Bd = Rolling element diameter, inches Pd = Pitch diameter, inches θ = Contact angle, degrees Fitting the parameters into the formula, we get BPFO multiplier = 3.052. This multiplier is used to obtain the fault frequencies for each RPM. VibraQuest enables the user to resize the block sizes to obtain different spectral resolution. The frequency spectral size can be up to 102,400 lines. This feature was helpful in finding the fault frequencies needed to diagnose the bearing faults in this experiment. Often a high resolution is needed to detect fault frequency, especially when the fault frequencies are very close to a multiple of the running speed. The following tables illustrate the resolution needed to detect bearing faults when fault frequencies are close to a multiple of the rotational speed for a Hanning Window function. If a different window is used, the resolution may have to be even higher.

Typical Spectra

Above is an illustration of typical spectra showing the outer race fault defect for 1000 RPM running speed. Note that there are several harmonics of running speed but the amplitudes are very small and the bearing fault amplitude is even smaller. A very high resolution is needed to detect outer race defects in the presence of third harmonic of running speed. The harmonics can happen due to many reasons, such as small unbalance, bearing clearance, machine non-linearity, etc. The resolution for this graph was 25,600 spectral lines.

Spectral Resolution Issue Spectral Resolution for 5,000 Hz Maximum Frequency Setting

Spectral Lines Resolution, Hz Resolution, RPM 100 50.0000 3,000.0000 200 25.0000 1,500.0000 400 12.5000 750.0000 800 6.2500 375.0000 1,600 3.1250 187.5000 3,200 1.5625 93.7500 6,400 0.7813 46.8750 12,800 0.3906 23.4375 25,600 0.1953 11.7188 51,200 0.0977 5.8594 102,400 0.0488 2.9297

Spectral Resolution Needed for Detecting Bearing Faults for MB ER-10K bearing at the Running Speed of 2,004 RPM using a Hanning Window

Notation Fault Frequency Multiplier

Fault Frequency (Hz)

Harmonics of the Running

Speed

Harmonic Frequencies

(Hz)

Delta Frequencies

(Hz)

Resolution to Detect the Fault Frequencies = Delta

Frequencies/4 (Hz) BPFI 4.9480 165.3176 5 167.0570 1.7394 0.4349 BFPO 3.0520 101.9704 3 100.2340 1.7364 0.4341 BSF 1.9920 66.5547 2 66.8230 0.2683 0.0671

RPM Harmonics

1 2 3 4 5 6 7 8 33.411 66.823 100.234 133.646 167.057 200.469 233.880 267.291

It can be seen from our table that extremely high resolution is needed to detect bearing faults and the leakages or spectral smearing is eminent in the analysis using conventional FFT Analyzers.

The graph above displays outer race bearing fault very close to third harmonic of RPM. A 25,600 lines of spectral resolution is needed to see the defect. The graph below shows the same data with 6,400 lines of spectral resolution. The fault frequency is between the two cursors and it is not possible to detect bearing defects due to the data smearing and poor resolution.

Rotor Weight, Speed, and Fault Severity Effects From these data, peak amplitudes of BPFO were obtained for a variety of cases. These amplitudes were then compiled to extract the information in 3 different ways: loading effects at same speed, rotating speed effects on same loading condition, and faulted level effects. These amplitudes are displayed on the following graphs. Loading Effects

Lightly faulted bearing The below four graphs are peak amplitudes of spectra at BPFO in horizontal and vertical direction of the inboard bearing at four different speeds of 1000 RPM, 1500 RPM, 2000 RPM, and 4000 RPM. One cannot see much clear-cut trained in the data – there is a scatter in the data. This indicates that rotor weight does not affect the amplitude of the BPFO fault. 1000RPM

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

No loader Inside loader 2 Loaders

Loading Condition

IBrgHIBrgV

1500RPM

0.00E+00

1.00E-05

2.00E-05

3.00E-05

4.00E-05

5.00E-05

6.00E-05

7.00E-05

No loader Inside loader 2 Loaders

Loading Condition

Am

plitu

de (g

)

IBrgH

IBrgV

2000RPM

0.00E+00

2.00E-05

4.00E-05

6.00E-05

8.00E-05

1.00E-04

1.20E-04

1.40E-04

1.60E-04

No loader Inside loader 2 Loaders

Loading Condition

Am

plitu

de (g

)

IBrgH

IBrgV

4000RPM

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

3.50E-04

4.00E-04

4.50E-04

No loader Inside loader 2 Loaders

Loading Condition

Am

plitu

de (g

)

IBrgH

IBrgV

Moderately faulted bearing The below four graphs are peak amplitudes of spectra at BPFO in horizontal and vertical direction of the inboard bearing at four different speeds of 1000 RPM, 1500 RPM, 2000 RPM, and 4000 RPM. One cannot see much clear-cut trained in the data – there is a scatter in the data. This indicates that rotor weight does not affect the amplitude of the BPFO fault. 1000RPM

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

No loader Inside loader 2 Loaders

Loading Condition

Am

plitu

de (g

)

IBrgH

IBrgV

1500RPM

0.00E+00

1.00E-05

2.00E-05

3.00E-05

4.00E-05

5.00E-05

6.00E-05

7.00E-05

8.00E-05

9.00E-05

1.00E-04

No loader Inside loader 2 Loaders

RPM

Am

plitu

de (g

)

IBrgH

IBrgV

2000RPM

0.00E+00

2.00E-05

4.00E-05

6.00E-05

8.00E-05

1.00E-04

1.20E-04

1.40E-04

1.60E-04

1.80E-04

2.00E-04

No loader Inside loader 2 Loaders

Loading Condition

Am

plitu

de (g

)

IBrgH

IBrgV

4000RPM

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

3.50E-04

4.00E-04

No loader Inside loader 2 Loaders

Loading Condition

Am

plitu

de (g

)

IBr

IBr

Rotating Speed Effects Lightly faulted bearing The below three graphs are peak amplitudes of spectra at BPFO in horizontal and vertical direction of the inboard bearing at four different speeds of 1000 RPM, 1500 RPM, 2000 RPM, and 4000 RPM with varying weights. One cannot see much clear-cut trained in the data – there is a scatter in the data. This indicates that rotor weight does not affect the amplitude of the BPFO fault. No loader

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

1000RPM 1500RPM 2000RPM 4000RPMRPM

Am

plitu

de (g

)

Inside loader

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

3.50E-04

4.00E-04

4.50E-04

1000RPM 1500RPM 2000RPM 4000RPM

RPM

Am

plitu

de (g

)

IBrgH

IBrgV

2 loaders

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

1000RPM 1500RPM 2000RPM 4000RPM

RPM

Am

plitu

de (g

)

IBrgH

IBrgV

Moderately faulted bearing The below three graphs are peak amplitudes of spectra at BPFO in horizontal and vertical direction of the inboard bearing at four different speeds of 1000 RPM, 1500 RPM, 2000 RPM, and 4000 RPM with varying weights. One cannot see much clear-cut trained in the data – there is a scatter in the data. This indicates that rotor weight does not affect the amplitude of the BPFO fault. No loader

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

3.50E-04

1000RPM 1500RPM 2000RPM 4000RPM

RPM

Am

plitu

de (g

)

IBrgH

IBrgV

Inside loader

0.00E+00

5.00E-05

1.00E-04

1.50E-04

2.00E-04

2.50E-04

3.00E-04

3.50E-04

4.00E-04

1000RPM 1500RPM 2000RPM 4000RPM

RPM

Am

plitu

de (g

)IBrgH

IBrgV

2 loaders

0.00E+00

2.00E-05

4.00E-05

6.00E-05

8.00E-05

1.00E-04

1.20E-04

1.40E-04

1000RPM 1500RPM 2000RPM 4000RPMRPM

Am

plitu

de (g

)

IBrgHIBrgV

Conclusions The results of the study seem to indicate that BPFO amplitude is not a strong function of speed, rotor weight, and fault severity within the range of this investigation. Using a high resolution, it should be possible to detect BPFO from the spectral analysis. The spectral resolution needed for detection will be a function of speed and type of bearing defect. The severity levels used for the bearing defect in this study were not high, so this study cannot be used conclusively for detecting bearing defect severity. The only focus of this study was to detect the fault using spectrum data. No other parameters such as RMS level, crest factor, or kurtosis, we were used to compare the results. The next study will perform further analysis on the data.