首页 | 官方网站   微博 | 高级检索  
     

基于贝叶斯网络的地铁牵引变电所可靠性分析
引用本文:何江海,裴卫卫,闫雅斌,鲁晓珊,邢宗义.基于贝叶斯网络的地铁牵引变电所可靠性分析[J].铁路计算机应用,2019,28(8):68-74.
作者姓名:何江海  裴卫卫  闫雅斌  鲁晓珊  邢宗义
作者单位:1. 广州地铁集团有限公司, 广州 510308;
基金项目:国家重点研发计划资助(2017YFB1201202)
摘    要:地铁牵引变电所作为城市轨道交通系统的关键环节,其可靠性研究对保障系统安全稳定运行有着重要意义。为了对地铁牵引变电所(简称:变电所)展开可靠性评估,利用GeNIE仿真软件,基于贝叶斯网络,构建了典型变电所静态下的可靠性模型,计算了变电所的初始故障概率;利用动态贝叶斯网络对典型变电所在时间维度上展开可靠性分析,精确地计算了变电所失效概率随时间变化的曲线;利用贝叶斯网络的双向推理功能找到变电所的薄弱环节,对变电所关键节点的识别、维护以及网络结构设计优化具有一定的意义。

关 键 词:牵引变电所    贝叶斯网络    可靠性
收稿时间:2018-07-08

Reliability analysis of metro traction substation based on Bayesian Network
Affiliation:1. Guangzhou Metro Group Co. Ltd., Guangzhou 510308, China;2. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
Abstract:As the key link of urban rail transit system, the reliability study of metro traction substation is of great significance to ensure the safe and stable operation of the system. In order to evaluate the reliability of the metro traction substation, this paper established reliability model of the typical metro traction substation based on Bayesian Network, calculated the initial failure probability of the system, used the Dynamic Bayesian Network to analyze the reliability of the typical metro traction substation in time dimension, and accurately calculated the curve of system failure probability with time. Finally, the paper used the two-way inference function of Bayesian Network to find the weak link of the system. It has certain significance for the identification, maintenance of key nodes and the optimization of network structure design in substation.
Keywords:
点击此处可从《铁路计算机应用》浏览原始摘要信息
点击此处可从《铁路计算机应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号