动车组PHM模型数据处理架构优化及关键技术研究

Data processing architecture optimization and key technology of EMU PHM model

摘要: 动车组故障预测与健康管理（PHM，Prognostics and Health Management）模型研究工作围绕动车组运维数据开展。数据是动车组PHM模型的驱动力，数据计算是动车组PHM模型的核心。文章从动车组PHM模型应用现状出发，对动车组PHM模型数据架构进行了优化设计，研究了动车组车载信息无线传输系统（WTDS ，Wireless Transmission Device System）数据清洗及存储等关键技术，提升了PHM模型源数据处理效率。

Abstract: The research work of Electric Multiple Unit(EMU) Prognostics and Health Management(PHM) model is carried out around EMU Operation and maintenance data. Data is the driving force of EMU PHM model, and data calculation is the core of EMU PHM model. Starting from the application status of EMU PHM model, this paper optimized the data architecture of EMU PHM model, studied the key technologies such as wireless transmission device system data cleaning and storage, and improved the source data processing efficiency of PHM model.