reviewIEEE Sensors JournalNov 8, 2023HYBRID OA

Rotating Machinery Fault Diagnosis Under Time-Varying Speeds: A Review

Beijing University of Technology · Beijing University of Chemical Technology

Indexed incrossref

Abstract

Rotating machinery often works under time-varying speeds, and nonstationary conditions as well as harsh environments make its key parts, such as rolling bearings and gears, prone to faults. Therefore, a number of fault diagnosis methods including nonstationary signal processing methods and data-driven methods have been developed. This paper presents a comprehensive review on the fault diagnosis of rotating machinery under time-varying speeds proposed mainly during the last five years. First, spectrum analysis-based methods, including order tracking, cyclic spectrum correlation and generalized demodulation, are reviewed. Second, the time-frequency analysis (TFA) methods in machinery fault diagnosis are divided…

Citation impact

190
total citations
FWCI
33.41
Percentile
100%
References
210
Citations per year

Authors

3

Topics & keywords

Keywords
  • Fault (geology)
  • Time–frequency analysis
  • Feature extraction
  • Computer science
  • Signal processing
  • Control engineering
  • Demodulation
  • Engineering
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