城市轨道交通综合监控运维报文智能解析工具设计与应用

Design and Application of an Intelligent Parsing Tool for Urban Rail Transit Integrated Supervisory Control Operation and Maintenance Messages

摘要: 城市轨道交通综合监控系统涉及十余个专业子系统，运维报文格式异构、解析依赖人工经验，导致故障定位效率低、准确率难保障，且报文涉及核心保密信息，无法使用联网工具辅助分析。针对上述问题，本文设计并实现了一套轻量化、本地部署的故障报文智能分析工具。该工具构建标准化解析规则库与寄存器地址映射数据集，实现报文专业自动判别与故障精准定位，并封装为单个独立可执行文件(约56 MB)，免安装、双击即用、完全离线运行。实验结果表明，工具单次报文解析平均耗时4.7分钟，较人工解析效率提升约92%，准确率达100%。工具核心知识库基于特定线路的厂商协议、点位表和历史报文构建，具有高度定制化特征，其设计方法可为同类项目提供借鉴。该方案为轨道交通行业提供了一种低成本、安全可控、方法可借鉴的智能解析工具，具有积极的实践推广价值。

Abstract: Urban rail transit integrated supervisory control systems involve more than ten professional subsystems, with operation and maintenance messages featuring heterogeneous formats and parsing heavily reliant on manual expertise. This leads to low fault localization efficiency, unsatisfactory accuracy, and the inability to use online tools due to the confidential nature of the messages. To address these issues, this paper designs and implements a lightweight, locally deployed intelligent message parsing tool. The tool builds a standardized parsing rule base and a register address mapping dataset, enabling automatic subsystem identification and precise fault localization. It is packaged as a single standalone executable file (approximately 56 MB) that requires no installation, runs with a double-click, and operates completely offline. Experimental results show that the average parsing time per message is 4.7 minutes, reducing the time by about 92% compared to manual parsing, with an accuracy rate of 100%. The core knowledge base is built based on the manufacturer protocols, point tables, and historical messages of a specific line, and is therefore highly customized; its design methodology can provide reference for similar projects. This solution provides the rail transit industry with a low-cost, safe, controllable, and methodologically referential intelligent parsing tool, offering significant practical value for broader adoption.