摘要
铁路供电故障预测与健康管理(PHM)系统是以大数据技术为核心,以供电管理信息系统、6C数据中心、SCADA系统为支撑,按照国铁集团-铁路局-供电段三级管理架构进行设计和建设的供电设备大数据分析管理平台。基于大数据框架的PHM系统涵盖针对高速铁路接触网和牵引变电所的PHM技术方案,在多时空尺度上实现铁路供电故障预测与健康指标评估,全生命周期可靠性、可用性和可维修性的可视化分析和风险评估,以及优化维修决策。本文阐述了铁路供电故障预测与健康管理大数据平台方案的基本设计原则和系统架构,并对该平台涉及的关键技术和系统重要功能进行了探讨。
The fault prognostics and health management(PHM)system for railway power supply equipment is based on big data technology,supported by the power management information system,6 C data center,and SCADA system,designed and formed according to the three-tier management structure of the National Railway Corporation-Railway Administration-Power Supply Section.The fault prognostics and health management system for railway power supply equipment is based on the big data platform,covering PHM system for high-speed railway catenary and PHM system for traction substation,to achieve railway power supply equipment fault prognostics and health index assessment on multiple time-space scales,visual analysis and risk assessment of availability,availability and maintainability in full life cycle,and optimization of maintenance decisions.This paper illustrates the basic design principles and system architecture of fault prognostics and health management big data platform for railway power supply equipment,and discusses the key technologies and the important functions of the big data platform.
作者
高金山
李银生
GAO Jinshan;LI Yinsheng
出处
《电气化铁道》
2021年第5期21-25,共5页
Electric Railway
关键词
故障预测
健康管理
大数据技术
检测监测
fault prognostics
health management
big data technology
inspection and monitoring
