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高速动车组大数据PHM系统研究与应用

Fault prognostics and health management system of high-speed EMU based on big data

  • 摘要: 针对延长高速动车组使用寿命和提高使用效率的问题,在研究了工业大数据、故障预测与健康管理(PHM)的定义和应用、PHM相关标准以及国外PHM软件开发平台的基础上,搭建了基于大数据的车载、地面故障预测与健康管理系统一体化的功能架构并提出技术实现方案,应用动车牵引电机轴承温度健康状态模型,以牵引电机轴承温度和环境温度数据为基础,进行了实例分析。

     

    Abstract: In order to prolong the service life and improve the efficiency of the high-speed EMU, the paper studied on the definition and application of industrial big data, fault prognostics and health management(PHM), PHM related standards and the foreign PHM software development platform, built up an integrated function structure of the ground and onboard fault prognostics and health management system based on big data, and put forward technical implementation plan. Based on the data of traction motor bearing temperature and ambient temperature, an example analysis was made on the temperature health state model of traction motor bearing.

     

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