Description

Book Synopsis
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.

Bayesian Networks In Fault Diagnosis: Practice

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Order before 4pm today for delivery by Mon 19 Jan 2026.

A Hardback by Baoping Cai, Yonghong Liu, Jinqiu Hu

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    View other formats and editions of Bayesian Networks In Fault Diagnosis: Practice by Baoping Cai

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 16/10/2018
    ISBN13: 9789813271487, 978-9813271487
    ISBN10: 9813271485
    Also in:
    Bayesian inference

    Description

    Book Synopsis
    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.

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