提高机务行车监测报警措施分析

Analysis on Improvement of Train Operation Monitoring and Alarming Measures

随着国家能源集团铁路运量的逐年提升,列车运行安全成为运输管理中最重要的环节。如何保障行车安全成为机务安全工作的重点,传统方法是通过对机车乘务员的培训教育,让其掌握更多的行车知识、树立安全意识思想来保障行车安全。该方法对乘务员个人素质要求较高,实际生产中很难做到机务段所有乘务员具备同样的思想和技术素养。所以需要从科技入手,设计一套基于视频的乘务员行为监测系统,保证司机在行车过程中按照操规、技规标准操纵,对于异常行为、精神状态欠佳、瞭望不及时等进行实时报警。文章通过对当前背景进行分析,针对需求通过机器学习方法实现行车过程中乘务员行为、精神状态等实时分析并报警,达到实时监测乘务员行车操纵是否标准化目的。通过试验表明,系统实现了乘务员全程行为监测并对异常行为进行报警。

As the railway traffic volume of CHN Energy has been improved year by year,the train opera⁃tion safety becomes an important link in the transport management,and how to ensure the operation safety becomes a key emphasis in the locomotive safety work.The traditional method is to ensure the operation safe⁃ty by training and educating the locomotive attendants to make them master more operation knowledge and maintain the safety awareness and thought.As this method has high requirements on the personal qualities of the attendants and all the attendants cannot obtain the same thought and technology literacy in practice,it is necessary to turn to technology to design a video-based attendant behavior monitoring system,thus en⁃suring that the driver can control the train according to the operation regulations and technical regulations and standards during the operation and that a real-time alarm can be given in case of abnormal behavior,poor mental state,no timely observation,etc.By analyzing the current background,this article realizes the real-time analysis and alarm on the behavior and mental state of the attendants during the operation in the method of machine learning according to the needs,thus achieving the goal of monitoring whether the opera⁃tion control of the attendants is standardized in real time.Besides,this article also shows through experi⁃ment that the system can monitor the behavior of the attendants in the whole course and give an alarm on abnormal behaviors.