NDLI: Fault Diagnosis Model of the Diesel Locomotive Air Brake System Based on Bayesian Network

Content Provider	IEEE Xplore Digital Library
Author	Hu Lingling Zhang Santong
Copyright Year	2010
Abstract	Due to the configuration complexity of the diesel locomotive air brake system, it is difficult to realize the fault diagnosis on the brake system. In order to enhance fault diagnosis efficiency for diesel locomotive air brake system with uncertain fault, a fault diagnosis model based on Bayesian network is proposed in this paper. According to a priori exact probability or experts estimate that the probability, the classical Expectation-Maximization algorithm calculates the joint fault probability distribution and probability distribution of marginal respectively. Based on joint tree algorithm, Bayesian network is designed to infer the fault probabilities of components. The fault location could be realized. The simulation results indicate that the accurate fault probabilities could be calculated. Therefore, this method is effective for uncertain fault.
Starting Page	1
Ending Page	3
File Size	228994
Page Count	3
File Format	PDF
ISBN	9781424487769
e-ISBN	9781424487783
DOI	10.1109/LEITS.2010.5664969
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Bayesian methods Atmospheric modeling Valves Probability distribution Joints
Content Type	Text
Resource Type	Article

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Fault Diagnosis Model of the Diesel Locomotive Air Brake System Based on Bayesian Network