Rolling element bearing defect detection using the generalized synchrosqueezing transform guided by time-frequency ridge enhancement

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107 Scopus citations

Abstract

Healthy rolling element bearings are vital guarantees for safe operation of the rotating machinery. Time-frequency (TF) signal analysis is an effective tool to detect bearing defects under time-varying shaft speed condition. However, it is a challenging work dealing with defective characteristic frequency and rotation frequency simultaneously without a tachometer. For this reason, a technique using the generalized synchrosqueezing transform (GST) guided by enhanced TF ridge extraction is suggested to detect the existence of the bearing defects. The low frequency band and the resonance band are first chopped from the Fourier spectrum of the bearing vibration measurements. The TF information of the lower band component and the resonance band envelope are represented using short-time Fourier transform, where the TF ridge are extracted by harmonic summation search and ridge candidate fusion operations. The inverse of the extracted TF ridge is subsequently used to guide the GST mapping the chirped TF representation to the constant one. The rectified TF pictures are then synchrosqueezed as sharper spectra where the rotation frequency and the defective characteristic frequency can be identified, respectively. Both simulated and experimental signals were used to evaluate the present technique. The results validate the effectiveness of the suggested technique for the bearing defect detection.

Original languageEnglish
Pages (from-to)274-284
Number of pages11
JournalISA Transactions
Volume60
DOIs
StatePublished - 2016

Bibliographical note

Funding Information:
This work is supported in part by the Prometeo Project of the Secretariat for Higher Education, Science, Technology and Innovation of the Republic of Ecuador , the National Natural Science Foundation of China ( 51375517 ), the Chongqing Basic and Frontier Research Project ( cstc2015jcyjA0158 ), and the Project of Chongqing Innovation Team in University ( KJTD201313 ). The valuable comments and suggestions from the reviewers are very much appreciated.

Funding Information:
This work is supported in part by the Prometeo Project of the Secretariat for Higher Education, Science, Technology and Inno- vation of the Republic of Ecuador, the National Natural Science Foundation of China (51375517), the Chongqing Basic and Frontier Research Project (cstc2015jcyjA0158), and the Project of Chongq- ing Innovation Team in University (KJTD201313). The valuable comments and suggestions from the reviewers are very much appreciated.

Publisher Copyright:
© 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Keywords

  • Defect detection
  • Generalized synchrosqueezing transform
  • Rolling element bearing
  • Short-time Fourier transform
  • Time-frequency ridge

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