Abnormal Vibration Fault Diagnosis of Reducer Based on Bayesian Network

Xin Tan, Jingshu Zhong, Xiaofeng Zhou, Zixin Wang, Anye Zhou, Yu Zheng

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

Abstract

In order to recognize the fault type of reducer abnormal vibration and reduce the cost of inspection and maintenance, an intelligent diagnosis model is developed. In the case of insufficient historical abnormal vibration data, a fault tree of the reducer is established by combing the historical fault data. It is then mapped to the Bayesian network structure. The expectation maximization (EM) algorithm is selected as the parameter learning method to determine the probability distribution of the node variables. After processing real-time vibration data, the model integrates the abnormal vibration feature discrimination mechanism and hierarchical Gibbs sampling algorithm to carry out fault probability inference. Compared with other models, the proposed model has achieved great improvement in the accuracy of diagnosis results and distinguishing normal and abnormal data. The model is integrated into the intelligent operation and maintenance system of belt conveyor for engineering verification.

Original languageEnglish
Title of host publicationAdvances in Neural Networks – ISNN 2024 - 18th International Symposium on Neural Networks, 2024, Proceedings
EditorsXinyi Le, Zhijun Zhang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages505-514
Number of pages10
ISBN (Print)9789819743988
DOIs
StatePublished - 2024
Externally publishedYes
Event18th International Symposium on Neural Networks, ISNN 2024 - Weihai, China
Duration: Jul 11 2024Jul 14 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14827 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Symposium on Neural Networks, ISNN 2024
Country/TerritoryChina
CityWeihai
Period07/11/2407/14/24

Keywords

  • abnormal vibration
  • Bayesian network
  • fault tree
  • Gibbs sampling
  • reducer

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