Bayesian Networks In Fault Diagnosis: Practice And Application

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.

Product details

• Authors: Yonghong Liu Jinqiu Hu Baoping Cai, Yonghong Liu Jinqiu Hu Ze Baoping Cai, Baoping Cai, Jinqiu Hu, Yonghong Liu
• Assisted by: Baoping Cai (Editor), Baoping Cai (Editor), Jinqiu Hu (Editor), Renjie Ji (Editor), Jinqiu Hu (Editor), Yonghong Liu (Editor), Zengkai Liu (Editor), Shengnan Wu (Editor), Yonghong Liu (Editor)
• Publisher: Ingram Publishers Services
• Languages: English
• Product format: Hardback
• Released: 31.01.2019
• EAN: 9789813271487
• ISBN: 978-981-3271-48-7
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / Bayesian Analysis, Bayesian Inference, Bayesian Networks, Fault Diagnosis