WANG Rui-feng， JIA Nan
（School of Automation & Electrical Engineering， Lanzhou Jiaotong University， Lanzhou 730070， China）
Abstract： Evaluation of the health state and prediction of the remaining life of the track circuit are important for the safe operation of the equipment of railway signal system. Based on support vector data description (SVDD) and gray prediction, this paper illustrates a method of life prediction for ZPW-2000A track circuit, which combines entropy weight method, SVDD, Mahalanobis distance and negative conversion function to set up a health state assessment model. The model transforms multiple factors affecting the health state into a health index named H to reflect the health state of the equipment. According to H, the life prediction model of ZPW-2000A track circuit equipment is established by means of gray prediction so as to predict the trend of health state of the equipment. The certification of the example shows that the method can visually reflect the health state and effectively predict the remaining life of the equipment. It also provides a theoretical basis to further improve the maintenance and management for ZPW-2000A track circuit.
Key words： track circuit; health state assessment; life prediction; support vector data description (SVDD); gray prediction
CLD number： U283.2 Document code： A
Article ID： 1674-8042（2018）04-0373-07 doi： 10.3969/j.issn.1674-8042.2018.04.011
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基于SVDD和灰色预测的ZPW-2000A轨道电路设备寿命预测研究
王瑞峰， 贾 楠
（兰州交通大学 自动化与电气工程学院， 甘肃 兰州 730070）
摘 要: 轨道电路作为铁路信号的重要基础设备， 对其进行健康状态评估和剩余寿命预测可以有效保障设备安全运行。 本文描述了基于支持向量数据描述法（support vector domain description, SVDD）和灰色预测的ZPW-2000A轨道电路寿命预测方法。 采用熵权法、 SVDD、 马氏距离和负向转换函数等建立健康状态评估模型， 将影响健康状态的多因素转化为反映轨道电路设备健康状态的指标， 即健康度H； 根据健康度， 建立基于灰色预测的ZPW-2000A轨道电路设备寿命预测模型， 预测健康状态未来的发展趋势。 实例验证表明， 该方法能直观地看出轨道电路设备健康状态水平， 并有效地预测设备的剩余寿命， 为进一步提高维修管理水平提供了理论依据。
关键词: 轨道电路； 健康状态评估； 寿命预测； 支持向量数据描述； 灰色预测
引用格式： WANG Rui-feng， JIA Nan. Life prediction of ZPW-2000A track circuit equipment based on SVDD and gray prediction. Journal of Measurement Science and Instrumentation, 2018, 9(4)： 373-379. ［doi： 10.3969／j.issn.1674-8042.2018.04.011］
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