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Predictive maintenance & condition monitoring


Figure 14. The Fourier plot with the dc spur removed and shown on a linear scale.


Figure 15. The X, Y, and Z vibration plots are separated out.


The simulation results of the faulty and nonfaulty motors are shown in Figure 13. The experiment was conducted on a motor rotating at 587.3 rpm with a bearing fault with the outer race misaligned and with a 12 pound load. The plots also show the vibration pattern of a motor with no fault rotating at the same speed. It is clear that the faulty motor has a significantly higher amplitude in the vibration signature compared with the nonfaulty motor. With the Waveform window highlighted,


select View > FFT from the menu bar. This will compute the FFT based on the transient data. Looking at the data in Figure 2, the


numbers show a small variation about a large offset of approximately 35,000. When simulated in LTspice, this translates to a dc offset voltage of 35,000 V with an ac


Instrumentation Monthly October 2020


waveform on top of this offset. In the Fourier plot, this offset voltage


manifests itself as a large spur at dc, so when LTspice autoscales the Y axis, the harmonics of interest are scaled too small. Right-click the X axis to specify a frequency range above dc, so the dc offset voltage is ignored—a range of 5 Hz to 1 kHz should suffice. Right-click the Y axis and select the Linear radio button to view the harmonics, as shown in Figure 14.


Right-clicking inside the plot area enables extra plot panes to be added, which enables the spectral content of the vibration to be separated into X, Y, and Z plots, as shown in Figure 15. The 10 Hz rotation frequency of the motor can clearly be seen, as well as significant harmonics at 60 Hz, 142 Hz, and 172 Hz. It is beyond the scope of this article to analyse


what component inside the motor has caused these harmonics, but there is no doubt that the vibration pattern has changed due to motor wear.


CONCLUSION Analog Devices’ range of MEMS accelerometers provide critical data to enable the early detection of motor failure, but that is only half the solution. The data must be carefully studied using Fourier analysis. Unfortunately, equipment or software capable of performing Fourier analysis is typically expensive. LTspice provides a free-of-charge route to accurately analyse CbM data, enabling the early detection and diagnosis of machine failure.


Analog Devices www.analog.com 21


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