Railway Vehicle Door Fault Diagnosis Method with Bayesian Network
Ruwen Chen, Songqing Zhu, Fei Hao, Bin Zhu, Zhendong Zhao, Youxiong Xu
Abstract
Ruwen Chen, Songqing Zhu, Fei Hao, Bin Zhu, Zhendong Zhao, Youxiong Xu
Abstract
Recent years, more attention has been given to fault diagnosis of railway vehicle door system. In order to handle the uncertainties in fault diagnosis of the door system, a fault diagnosis method based on Bayesian Network was proposed. Fault data provided by a subway company was counted. A model based on Bayesian Network of railway vehicle door was built up and the prior probability of failure was calculated. Inputting fault evidence in the Bayesian model, the posterior probability of each fault would be obtained. Simulation experiment and engineering application show that Bayesian Network can reason through the fault of door system correctly and the result can provide reference and advice for fault diagnosis and maintenance of railway vehicle door.
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Recent years, more attention has been given to fault diagnosis of railway vehicle door system. In order to handle the uncertainties in fault diagnosis of the door system, a fault diagnosis method based on Bayesian Network was proposed. Fault data provided by a subway company was counted. A model based on Bayesian Network of railway vehicle door was built up and the prior probability of failure was calculated. Inputting fault evidence in the Bayesian model, the posterior probability of each fault would be obtained. Simulation experiment and engineering application show that Bayesian Network can reason through the fault of door system correctly and the result can provide reference and advice for fault diagnosis and maintenance of railway vehicle door.
Key concepts: Bayesian network, Fault (geology), Bayesian probability, Computer science, Bayesian inference, Fault model, Reliability engineering, Engineering