摘要
针对高铁牵引系统结构复杂、退化参数较多、失效阈值难以确定等问题,提出了一种基于性能退化的剩余寿命预测方法.首先,提取退化参数的多种统计特征,通过单调性指标、相关性指标、冗余性指标进行特征选择,减少冗余、无关特征的干扰;在缺少失效阈值的情况下,提出一种基于健康状态的策略,通过评估系统的健康状态,判断系统是否失效;然后利用选择的特征训练长短期记忆网络进行退化轨迹预测;最后,在高铁牵引系统半物理实验平台上以中间电路电容性能退化为案例进行算法有效性的验证,结果表明该方法优于现有方法.
To address the problems of complex structures,complicated performance degradation parameters,and missing failure threshold,we propose a remaining useful life(RUL)prediction method based on performance degradation.First,we extract various statistical features of degraded parameters,and perform feature selection using monotonic,related,and redundancy indexes to reduce the interference of redundant and irrelevant features.We propose a health-based strategy that assesses the system failure condition by assessing the health of the system to predict RUL without a failure threshold.Then,we use the selected features to train long-and short-term memory networks for degraded trajectory prediction.We conduct a case study using a hardware-in-the-loop simulation platform for the traction system of Chinese railway high-speed trains to predict the RUL of the DC-link circuit with capacitance degradation.Experimental results show the validity and superiority of the proposed method.
作者
朱凯强
陆宁云
姜斌
ZHU Kaiqiang;LU Ningyun;JIANG Bin(College of Automation Engineering,Nanjing University of Aeronautics&Astronautics,Nanjing 210016,China)
出处
《信息与控制》
CSCD
北大核心
2020年第3期335-342,共8页
Information and Control
基金
国家自然科学基金资助项目(61490703,61873122)。
作者简介
朱凯强(1995-),男,硕士生,研究领域为故障预测;通信作者:陆宁云(1977-),女,教授,博士生导师,研究领域为故障预测与健康管理,E-mail:luningyun@nuaa.edu.cn;姜斌(1966-),男,教授,博士生导师,研究领域为故障诊断与容错控制。
