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

Fingerprint

Bearings (structural)
Rotating machinery
Failure analysis
Feature extraction

Cite this

@article{caae74f22942473b8e309fa6c05541bb,
title = "A novel fault diagnosis method for rotating machinery based on S transform and morphological pattern spectrum",
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.",
keywords = "Rotating machinery, Bearing, Fault diagnosis , S transform, Morphological pattern spectrum",
author = "Jingwei Gao and Ruichen Wang and Rui Zhang and Yuan Li",
year = "2016",
month = "8",
doi = "10.1007/s40430-015-0474-6",
language = "English",
volume = "38",
pages = "1575--1584",
journal = "Journal of the Brazilian Society of Mechanical Sciences and Engineering",
issn = "1678-5878",
publisher = "Brazilian Society of Mechanical Sciences and Engineering",
number = "6",

}

A novel fault diagnosis method for rotating machinery based on S transform and morphological pattern spectrum. / Gao, Jingwei; Wang, Ruichen; Zhang, Rui; Li, Yuan.

In: Journal of the Brazilian Society of Mechanical Sciences and Engineering, Vol. 38, No. 6, 08.2016, p. 1575-1584.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A novel fault diagnosis method for rotating machinery based on S transform and morphological pattern spectrum

AU - Gao, Jingwei

AU - Wang, Ruichen

AU - Zhang, Rui

AU - Li, Yuan

PY - 2016/8

Y1 - 2016/8

N2 - 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.

AB - 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.

KW - Rotating machinery

KW - Bearing

KW - Fault diagnosis

KW - S transform

KW - Morphological pattern spectrum

U2 - 10.1007/s40430-015-0474-6

DO - 10.1007/s40430-015-0474-6

M3 - Article

VL - 38

SP - 1575

EP - 1584

JO - Journal of the Brazilian Society of Mechanical Sciences and Engineering

JF - Journal of the Brazilian Society of Mechanical Sciences and Engineering

SN - 1678-5878

IS - 6

ER -