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牵引供电设备健康及预测系统在京张高速铁路的应用研究 被引量:1

Application Research of Traction Power Supply Equipment Prognostic and Health Management to Beijing-Zhangjiakou High-speed Railway
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摘要 牵引供电设备健康及预测系统(PHM)是利用牵引供电设备的全生命周期数据,采用大数据技术对设备及零部件进行健康管理和故障预测的系统。通过建立可靠性、可用性、可维修性二级健康指标体系,并结合层次分析法、熵权法等主客观方法确定设备健康度计算模型的关键指标及权重系数,进行状态分级与分类;挖掘分析维修、检测、监测的原始数据和缺陷数据,并根据数据实际情况在时间序列预测模型、贝叶斯网络模型基础上进行深入应用,预测供电设备缺陷变化规律和设备故障。最终自动形成接触网系统及零部件的维修策略,全面提高接触网维修效率,提升运行可靠性,降低维护成本。 Traction power supply equipment prognostic and health management(PHM)is a system that utilizes the whole life cycle data of traction power supply equipment and big data technology to carry out the health management and the fault prediction for equipment and parts.Through the establishment of the two-tier health index system of reliability,av ailability and maintainability,combined with the subjective and objective methods such as AHP and entropy weight method are used to detemine the weight coefficient of the calculation model of equipment health degree,assess the health of power supply equipment.The original data and defect data of maintenance and inspection are mined and analyzed to carry out in depth application on the basis of the time series prediction model and Bayesian network model according to the actual situation of the data,which can predict the development law of power supply equipment defects and equipment failures.In the end,a maintenance strategy for the catenary system and parts will be automatically fommed,which will comprehensively improve the maintenance effciency of the catenary,improve operational reliability,reduce maintenance costs,and lay the foundation for building an intelligent operation and maintenance system for traction power supply.
作者 张裔 王广冬 Zhang Yi;Wang Guangdong(Beijing Eletrifcation Engineering C0.,LTD.of China Electrifcation Bureau(Group),Beijng 100036,China)
出处 《铁道技术标准(中英文)》 2023年第4期15-21,共7页 Railway Technical Standard(Chinese & English)
关键词 京张高速铁路 牵引供电 健康及预测系统 应用研究 Bejjing Zhangjakou high-speed railway traction power supply PHM application and technology research
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