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Time-extracting S-transform algorithm and its application in rolling bearing fault diagnosis 被引量:6
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作者 XU YongGang WANG Liang +1 位作者 HU AiJun YU Gang 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2022年第4期932-942,共11页
Time-frequency(TF)analysis(TFA)is one of the effective methods to deal with non-stationary signals.Due to their advantages,many experts and scholars have recently developed post-processing algorithms based on traditio... Time-frequency(TF)analysis(TFA)is one of the effective methods to deal with non-stationary signals.Due to their advantages,many experts and scholars have recently developed post-processing algorithms based on traditional TFA.Among them,shorttime Fourier transform(STFT)based post-processing algorithms have developed the fastest.However,these methods rely heavily on the window length selected in STFT,which has great influence on the post-processing algorithm.In this paper,a postprocessing algorithm for effectively processing pulse signals was proposed and called time-extracting S-transform(TEST).The time-domain extraction method based on S-transform avoids the influence of uncertain parameters.After comparing the performance of various TFA methods when processing analog signals,the proposed TEST can clearly show the pulse occurrence time under the premise of ensuring high TF aggregation.The actual signal proves that the method can be used for fault diagnosis of rolling bearings. 展开更多
关键词 time-extracting S-transform time-frequency analysis pulse signal fault diagnosis short-time Fourier transform
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