Matching Synchrosqueezing Wavelet Transform and Application to Aeroengine Vibration Monitoring

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179 Scopus citations

Abstract

This paper presents a new time-frequency (TF) analysis method called matching synchrosqueezing wavelet transform (MSWT) to signals with fast varying instantaneous frequency (IF). The original synchrosqueezing wavelet transform (SWT) can effectively improve the readability of TF representation (TFR) of signals with slowly varying IF. However, SWT still suffers from TF blurs for signals with fast varying IF. Moreover, the variable operating conditions of the aeroengine always make the vibration a signal with fast varying IF, especially when it comes to significant speed changes, which results in the obscure TFR for aeroengine vibration monitoring. In this paper, the MSWT introduces a chirp rate estimation into a comprehensive IF estimation to match the TF structure of the signals with fast varying IF and thus to achieve a highly concentrated TFR as the standard TF reassignment methods. Most importantly, the MSWT retains the reconstruction benefit like the SWT. The proposed MSWT is validated by both numerical simulation and applications in a bat echolocation signal analysis. Finally, a case study of a dual-rotor turbofan engine is given to illustrate the effectiveness of the proposed method for aeroengine vibration monitoring.

Original languageEnglish
Article number7765057
Pages (from-to)360-372
Number of pages13
JournalIEEE Transactions on Instrumentation and Measurement
Volume66
Issue number2
DOIs
StatePublished - Feb 2017

Keywords

  • Aeroengine
  • condition monitoring
  • fault diagnosis
  • synchrosqueezing
  • time-frequency (TF) analysis

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