A novel fault diagnosis method for rotating machinery based on S transform and morphological pattern spectrum

Jingwei Gao, Ruichen Wang, Rui Zhang, Yuan Li

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

With the continuing expansion of the applications of rotating machinery, an earlier and more accurate fault diagnosis method is required. In this paper, a novel characterization method based on S transform and morphological pattern spectrum (ST-MPS) was put forward. In order to verify the application of the method, ST-MPS was applied to a set of experimental signals obtained in a bearing test bench, and the results verified that the proposed feature extraction method is an effective approach to accurately classify the types of bearing fault.
Original languageEnglish
Pages (from-to)1575-1584
Number of pages10
JournalJournal of the Brazilian Society of Mechanical Sciences and Engineering
Volume38
Issue number6
Early online date26 Dec 2015
DOIs
Publication statusPublished - Aug 2016

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