中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (8): 108-113.doi: 10.16265/j.cnki.issn1003-3033.2026.08.0310

• 安全技术与工程 • 上一篇    下一篇

高速磁浮列车安全运行综合监控模型

胡启洲(), 雷爱国, 王晨   

  1. 南京理工大学 自动化学院, 江苏 南京 210094
  • 收稿日期:2026-04-14 修回日期:2026-06-20 出版日期:2026-08-28
  • 作者简介:

    胡启洲 (1975—),男,甘肃白银人,博士,副教授,主要从事交通信息工程与控制、智能交通及交通环境监测等方面的研究。E-mail:

  • 基金资助:
    江苏省“六大人才高峰”高层次人才项目(JXQC-021)

Comprehensive monitoring model for safe operation of high-speed maglev trains

Hu Qizhou(), Lei Aiguo, Wang Chen   

  1. School of Automation, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China
  • Received:2026-04-14 Revised:2026-06-20 Published:2026-08-28

摘要:

为实时监测高速磁浮列车在复杂环境中安全运行状态并评估风险,首先,采用数据驱动方法,基于多源异构运行数据,融合故障模式影响分析法(FMEA)和概率风险分析法(PRA),建立高速磁浮列车安全运行监控模型;其次,通过列车悬浮间隙、牵引电流、运行姿态、轨道状态等关键物理量的特征提取与分析,综合评估安全数据并识别异常行为;最后,提出主客观因素结合的综合监控方法,设计监控指标权重确定及危险等级划分方案,并通过3列高速磁浮列车监控试验验证。结果表明:3列高速磁浮列车的综合监控值分别为0.988 4、0.961 5和0.984 8,均处于五级(稍有危险)区间,运行状态总体安全;不同监控指标对应的致命度和风险值存在差异,悬浮间隙、牵引电流等关键指标对运行风险影响较为明显;监控系统具备列车运行状态监测、故障跟踪、日志告警及气象预警等功能,可反映列车运行风险变化。

关键词: 高速磁浮列车, 安全运行, 综合监控, 故障模式影响分析法(FMEA), 概率风险分析法(PRA)

Abstract:

To realize real-time monitoring and risk assessment of the safe operation status of high-speed maglev trains in complex environments, this study adopted a data-driven approach based on multi-source heterogeneous operational data and integrated FMEA and PRA to establish a safety operation monitoring model for high-speed maglev trains. Key physical parameters, including levitation gap, traction current, train attitude, and track conditions, were extracted and analyzed to achieve comprehensive safety evaluation and abnormal behavior identification. Furthermore, a combined subjective-objective monitoring method was proposed, together with procedures for determining monitoring indicator weights and defining hazard levels. The proposed model was validated through monitoring experiments on three high-speed maglev trains. The results show that the comprehensive monitoring values of the three trains are 0.988 4, 0.961 5, and 0.984 8, respectively, all falling within the Level V (slightly dangerous) interval, which indicates the overall safe operation state of the trains. Significant differences are observed in the criticality and risk values corresponding to different monitoring indicators, among which levitation gap and traction current exhibit relatively greater impacts on operational risk. In addition, the monitoring system is capable of performing train operation status monitoring, fault tracking, log alarming, and meteorological warning, while effectively reflecting changes in operational risk.

Key words: high-speed maglev train, safe operation, comprehensive monitoring, failure mode and effects analysis (FMEA), probabilistic risk assessment (PRA)

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