Time-extracting S-transform algorithm and its application in rolling bearing fault diagnosis  

作　　者：XU YongGang WANG Liang HU AiJun YU Gang 

机构地区：[1]Beijing Engineering Research Center of Precision Measurement Technology and Instruments,Faculty of Materials and Manufacturing,Beijing University of Technology,Beijing 100124,China [2]Department of Mechanical Engineering,North China Electric Power University,Baoding 071003,China [3]School of Electrical Engineering,University of Jinan,Jinan 250022,China

出　　处：《Science China(Technological Sciences)》2022年第4期932-942,共11页中国科学（技术科学英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos. 51775005 and 51675009)

摘　　要：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.

关 键 词：time-extracting S-transform time-frequency analysis pulse signal fault diagnosis short-time Fourier transform 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置] TH133.33[自动化与计算机技术—控制科学与工程]