Processing for Improved Spectral Analysis

Eric Bechhoefer, Brandon Van Hecke, and David He
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Full Paper
phmc_13_006.pdf688.43 KBOctober 11, 2013 - 1:10pm

The Fast Fourier Transform (FFT) is the workhorse of condition monitoring analysis. The FFTs’ assumption of stationarity is often violated in rotating machinery. Even in a six second acquisition on a wind turbine, the shaft speed can change by 5%. For Shaft and Gear analysis, this is mitigated through the use of the time synchronous average. For general spectrum analysis, or bearing envelope analysis, there is no such mitigation: one hopes that the effect of variation in shaft speed is small. Presented is a time synchronous resampling algorithm which corrects for variation in shaft speed, preserving the assumption of stationarity. This allows for improved spectral analysis, such as used in bearing fault detection. This is demonstrated on a real world-bearing fault.

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Submission Keywords: 
Bearing Analysis
Spectral Analysis
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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