Vibration signal-based early fault prognosis: Status quo and applications

Yaqiong Lv, Wenqin Zhao, Zhiyao Zhao, Weidong Li, Kam K.H. Ng

Research output: Journal article publicationReview articleAcademic researchpeer-review

87 Citations (Scopus)

Abstract

To implement Prognostics and Health Management (PHM) for industrial systems, it is paramount to conduct early fault prognosis on the systems to ensure the stability and reliability during their entire lifecycles. Investigations on early fault prognosis have been actively carried out, but there is a lack of systematic analysis and summary of the developed methods. To bridge the gap, in this paper, the relevant methods are comprehensively reviewed from the aspects of signal processing and fault identification. Furthermore, the applications of the methods are systematically described. In the end, to further facilitate researchers and practitioners, statistical and comparative analysis of the reviewed methods are given, and future development directions are outlined.

Original languageEnglish
Article number101609
JournalAdvanced Engineering Informatics
Volume52
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Deep learning
  • Early fault prognosis
  • Signal processing
  • Vibration signal analysis

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence

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