城市轨道交通CBTC系统实时故障定位方法
白广争郑泽熙冯浩楠许展瑛刘海祥范楷
Real-time Fault Locating Method for Urban Rail Transit CBTC System
BAI GuangzhengZHENG ZexiFENG HaonanXU ZhanyingLIU HaixiangFAN Kai
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作者信息:中国铁道科学研究院集团有限公司通信信号研究所， 100081， 北京
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Affiliation:Signal and Communication Research Institute of China Academy of Railway Sciences Group Co., Ltd., 100081, Beijing, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2024.02.021
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中图分类号/CLCN:U284.48
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栏目/Col:研究报告
摘要:
［目的］为了实现城市轨道交通CBTC(基于通信的列车控制)系统的快速故障诊断和定位，针对系统网络监测数据，提出一种基于时间约束的实时故障监测定位方法。［方法］介绍了所提CBTC系统实时故障定位方法的设计思路；提出了基于时间约束的故障定位算法；构建了CBTC数据监测系统，并进行了算法验证。［结果及结论］通过定义故障匹配模式，构建故障模式库，描述模式匹配规则并定义模式相似度；考虑CBTC系统中各子系统的通信周期、故障响应时间等功能需求方面的差异性，以及多系统之间的数据处理存在同步问题等，加入时间约束因素，时间约束以外的字符不能参与故障模式匹配；利用每次循环匹配失败点的位置，通过继承已匹配成功字符的信息，提高下一次匹配的效率，避免算法的回溯搜索，提高模式匹配效率。算法验证结果表明，所提算法能够快速、准确地定位系统中实时发生的故障。
Abstracts:
［Objective］ To carry out rapid fault diagnosis and locating for urban rail transit CBTC (communication-based train control) system, a real-time fault monitoring and locating method based on time constraints is proposed, focusing on system network monitoring data. ［Method］ The design concept of the proposed real-time fault locating method for the CBTC system is introduced. An algorithm based on time constraints for fault locating is proposed. A CBTC data monitoring system is constructed, and the algorithm is validated. ［Result & Conclusion］ By defining fault matching patterns, a fault pattern library is constructed, pattern matching rules are described, and pattern similarity degree is defined. Considering the differences in functional requirements, such as communication cycles and fault response time among various sub-systems in the CBTC system, and the synchronization issues in data processing among multiple systems, the time constraint factors are introduced, and characters beyond the specified time constraints are excluded from participating in fault pattern marching. Through utilizing the position of each failed matching point in the cycle and inheriting information of characters from successful matches, the efficiency of the next match is enhanced and backtracking searches by the algorithm are avoided, improving overall pattern matching efficiency. The algorithm validation results demonstrate that the proposed algorithm can rapidly and accurately locate real-time faults occurring in the system.
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