A New Fault Diagnosis Method Based on Belief Rule Base With Attribute Reliability Considering Multi-Fault Features
Author:
Affiliation:
1. School of Computer Science and Information Engineering, Harbin Normal University, Harbin, China
2. High-Tech Institute of Xi’an, Xi’an, China
3. High-Tech Institute, Qingzhou, China
Funder
Postdoctoral Science Foundation of China
Teaching Reform Project of Higher Education in Heilongjiang Province
Natural Science Foundation of Heilongjiang Province
Social Science Foundation of Heilongjiang Province of China
Foreign Expert Projects in Heilongjiang
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10232969.pdf?arnumber=10232969
Reference34 articles.
1. Hidden Markov model based principal component analysis for intelligent fault diagnosis of wind energy converter systems
2. A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests
3. A new safety assessment model for complex system based on the conditional generalized minimum variance and the belief rule base
4. A new approach to power system fault diagnosis based on fuzzy temporal order Petri nets
5. Knowledge-Based Fault Diagnosis in Industrial Internet of Things: A Survey
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1. A novel game-based belief rule base;Expert Systems with Applications;2024-11
2. Fault Diagnosis of High-Speed Train Motors Based on a Multidimensional Belief Rule Base;IEEE Access;2024
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