Fault feature extraction from time-frequency spectrum by using similarity measurement

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Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (12) : 70-77.

GUO Yuanjing1，WEI Yanding2，JIN Xiaohang3，LIN Yong1

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Abstract

A fault-related feature extraction method, which is based on the analysis of time-frequency spectrum by using similarity measurement, is proposed for gear or bearing fault diagnosis. In this approach, the time domain vibration signal is transformed into time-frequency domain by using S transform. Then, a noticeable impact feature is selected and keeping its frequency constant, translated from the initial time of the time-frequency spectrum along the time axis to the end time, while the cosine similarity coefficient and the correlation coefficient between the impact feature and its masked block in the spectrum are calculated. After that, a cosine similarity coefficient curve and a correlation coefficient curve are got. Finally, fault-related features can then be extracted clearly with the analysis of the frequency spectrum of the two time series coefficient data.

Key words

fault diagnosis / impact feature / S transform / cosine similarity coefficient / correlation coefficient

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GUO Yuanjing1，WEI Yanding2，JIN Xiaohang3，LIN Yong1. Fault feature extraction from time-frequency spectrum by using similarity measurement[J]. Journal of Vibration and Shock, 2020, 39(12): 70-77

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