4.7 Article

Use of cyclostationary properties of vibration signals to identify gear wear mechanisms and track wear evolution

期刊

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.107258

关键词

Fatigue pitting; Abrasive wear; Cyclostationary; Vibration signal; Wear mechanism identification; Wear monitoring

资金

  1. Australian Government through the Australian Research Council [DP160103501]
  2. China Scholarship Council [201706070120]

向作者/读者索取更多资源

A vibration-based wear mechanism identification method is proposed in this paper, which tracks the evolution of fatigue pitting and abrasive wear through the gearmesh-modulated properties of vibration signals. The effectiveness of this method in identifying and tracking fatigue pitting and abrasive wear has been validated in lubricated and dry tests.
Fatigue pitting and abrasive wear are the most common wear mechanisms in lubricated gears, and they have different effects on the gear transmission system. To develop effective methods for online gear wear monitoring, in this paper, a vibration-based wear mechanism identification procedure is proposed, and then the wear evolution is tracked using an indi-cator of vibration cyclostationarity (CS). More specifically, with consideration of the underlying physics of the gear meshing process, and the unique surface features induced by fatigue pitting and abrasive wear, the correlation between tribological features of the two wear phenomena and gearmesh-modulated second-order cyclostationary (CS2) properties of the vibration signal is investigated. Differently from previous works, the carrier frequencies (spectral content) of the gearmesh-cyclic CS2 components are analysed and used to distinguish and track the two wear phenomena. The effectiveness of the developed methods in wear mechanism identification and degradation tracking is validated using vibration data collected in two tests: a lubricated test dominated by fatigue pitting and a dry test dominated by abrasive wear. This development enables vibration-based techniques to be used for identifying and tracking fatigue pitting and abrasive wear. (c) 2020 Elsevier Ltd. All rights reserved.

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