摘要
在高铁动车组的故障预测与健康管理系统设计中,采用传统数据库或单一的大数据平台难以达到系统精确预测故障的业务功能设计的准确度要求,PHM大数据架构设计需综合考虑海量数据的膨胀、数据协议的复杂度、在线机理模型的变化以及机器学习的训练等因素。本文基于多组件的大数据生态技术分层架构体系进行设计与实现,详细阐述了高铁动车组的故障预测与健康管理大数据平台架构设计的方法和实现过程。
In the fault prediction of high-speed EMU and health management system design, the accuracy requirements of business function design using big data platform for traditional database or single system is difficult to achieve the accurate prediction of the fault, the design of PHM large data structure should be considered in massive data expansion, data protocol complexity, online mechanism model Type changes and machine learning training and other factors. In this paper, the hierarchical architecture system of big data components of ecological technology based on the design and implementation, and describes the methods for fault prediction of high-speed EMU and health management of big data platform architecture design and implementation process.
引文
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