|本期目录/Table of Contents|

[1]朱斌,陈茹雯,许有熊,等.基于贝叶斯网络的轨道车辆门故障诊断研究[J].南京工程学院学报(自科版),2017,15(02):40-44.[doi:10.13960/j.issn.1672-2558.2017.02.007]
 ZHU Bin,CHEN Ru-wen,XU You-xiong,et al.Research on Fault Diagnosis of Railway Vehicle Doors Based on Bayesian Network[J].Journal of Nanjing Institute of Technology(Natural Science Edition),2017,15(02):40-44.[doi:10.13960/j.issn.1672-2558.2017.02.007]
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《南京工程学院学报(自科版)》[ISSN:1672-2558/CN:SN32-1671/N]

卷:
第15卷
期数:
2017年02期
页码:
40-44
栏目:
出版日期:
2017-06-30

文章信息/Info

Title:
Research on Fault Diagnosis of Railway Vehicle Doors Based on Bayesian Network
作者:
朱斌陈茹雯许有熊朱松青
南京工程学院汽车与轨道交通学院, 江苏 南京 211167
Author(s):
ZHU Bin CHEN Ru-wen XU You-xiong ZHU Song-qing
School of Automotive and Rail Transit, Nanjing Institute of Technology, Nanjing 211167, China
关键词:
贝叶斯网络 轨道车辆门 故障诊断 先验概率 后验概率
Keywords:
Bayesian network railway vehicle door fault diagnosis prior probability posterior probability
分类号:
U268.3
DOI:
10.13960/j.issn.1672-2558.2017.02.007
文献标志码:
A
摘要:
轨道车辆门系统的故障诊断受到广泛关注.针对门系统在故障诊断中存在不确定性问题,提出一种基于贝叶斯网络的故障诊断流程,统计某地铁公司提供的故障数据,建立轨道车辆门故障贝叶斯网络模型,计算得出各故障的先验概率,在建立的贝叶斯模型中输入故障证据,得到各故障的后验概率.通过仿真试验证明了贝叶斯网络能很好地推理出门系统的故障所在,为车门的故障诊断和维修提供参考和建议.
Abstract:
Fault diagnosis of a railway vehicle door system is attracting considerable attention. In order to handle the uncertainties in fault diagnosis of a door system, a fault diagnosis flow based on Bayesian network was proposed. Fault data provided by a subway company was studied. A model based on Bayesian network of railway vehicle door was then built and the prior probability of failure was calculated. Input fault evidence in the Bayesian model, the posterior probability of each fault was obtained. The experimental simulation shows that Bayesian network can do a good job in reasoning through the fault of door system and the result can provide reference and advice for fault diagnosis and maintenance of railway vehicle doors.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-01-05; 修回日期: 2017-01-16
基金项目: 江苏省科技支撑计划项目(BE2014142); 江苏省自然科学基金项目(SBE2014000615)
作者简介: 朱斌,硕士研究生,研究方向为轨道车辆门系统故障诊断,E-mail: 353350519@qq.com
更新日期/Last Update: 2017-04-20