Electric Machine Fault Diagnosing Based on Energy Spectrum of Gauss Chirplet Transforms
Yongjun Tu · Gaoya dianqi · 2005
In this paper, a new method of diagnosing electric machine fault, which based on gauss chirplet transforms, is presented. Chirplet transforms (CTs) are variation of the time, the frequency, and the scale of the signal. CTs have more effective than wavelet transforms in time-frequency analyzing of non-stable signals. Energy spectrums of electric machine fault signal can be gauged by using Gauss CTs, so the frequencies of the signal can be extracted. Experiment results show this method is more concentrated in energy than fourier transform and wavelet transform.