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Bayesian Networks In Fault Diagnosis: Practice And Application

Authors :
Baoping Cai
Yonghong Liu
Jinqiu Hu
Zengkai Liu
Shengnan Wu
Renjie Ji
Baoping Cai
Yonghong Liu
Jinqiu Hu
Zengkai Liu
Shengnan Wu
Renjie Ji
Publication Year :
2019

Abstract

Fault diagnosis is useful for technicians to detect, isolate, identify faults, and troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals with various uncertainty problems. This model is increasingly utilized in fault diagnosis.This unique compendium presents bibliographical review on the use of BNs in fault diagnosis in the last decades with focus on engineering systems. Subsequently, eleven important issues in BN-based fault diagnosis methodology, such as BN structure modeling, BN parameter modeling, BN inference, fault identification, validation, and verification are discussed in various cases.Researchers, professionals, academics and graduate students will better understand the theory and application, and benefit those who are keen to develop real BN-based fault diagnosis system.

Details

Language :
English
ISBNs :
9789813271487 and 9789813271494
Database :
eBook Index
Journal :
Bayesian Networks In Fault Diagnosis: Practice And Application
Publication Type :
eBook
Accession number :
1887208