Weak Fault Enhancement Method for Bearing Fault Diagnosis by Using MWS Stochastic Resonance

Chao Zhang, Haoran Duan, Jianguo Wang, Fengshou Gu, Biao Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Large mechanical equipment is subject to periodic vibrations in harsh operating environments for a long time. Bearing failure produces violent changes in the behaviors of large rotating machinery as the safety and reliability of the scene. Therefore, it is especially significant to effectively identify the early failure of the bearing. Since the signal of bearing fault belongs to a low-frequency weak fault, it is hard to classify the characteristic frequency. To solve this shortcoming, a new stochastic resonance model MWS, which is established on the joint monostable function and Woods-Saxon, is presented and used to strengthen the characteristics frequency, also the bearing fault characteristic frequency is gained. The simulation analysis shows that the proposed method can effectively extract the weak fault characteristics which are submerged in the noisy environment, and the bearing test proves that the MWS effectively extract the weak feature information in the bearing fault signal.

Original languageEnglish
Title of host publicationProceedings of IncoME-V & CEPE Net-2020
Subtitle of host publicationCondition Monitoring, Plant Maintenance and Reliability
EditorsDong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Pages541-549
Number of pages9
Volume105
Edition1st
ISBN (Electronic)9783030757939
ISBN (Print)9783030757922
DOIs
Publication statusPublished - 16 May 2021
Event5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China
Duration: 23 Oct 202025 Oct 2020
Conference number: 5
https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

NameMechanisms and Machine Science
Volume105
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

Conference5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated titleIncoME-V and CEPE Net-2020
CountryChina
CityZhuhai
Period23/10/2025/10/20
Internet address

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