1.Zhijiang College, Zhejiang University of Technology, Shaoxing 312030, China;
2.Zhejiang Province Key Laboratory of Advanced Manufacturing Technology, Zhejiang University, Hangzhou 310027, China;
3.Key Laboratory of Special Purpose Equipment and Advanced Processing Technology of Ministry of Education, Zhejiang University of Technology, Hangzhou 310023, China
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.
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