基于数据的机车牵引变流器故障预测及安全对策研究

项目名称： 基于数据的机车牵引变流器故障预测及安全对策研究

项目编号： No.61273174

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 赵金

作者单位： 华中科技大学

项目金额： 82万元

中文摘要： 机车牵引变流器作为一个复杂非线性系统，其各部件故障的提前预警以及安全对策直接关系到整个高速铁路的行车安全。本项目以信号处理技术、故障预测模型、安全对策为研究内容，基于系统的历史数据、当前数据和专家经验信息等，以故障预测技术为途径，以小波变换、支持向量机、马尔可夫决策等理论和技术为手段，建立基于数据的机车牵引变流器故障预测及安全对策方法。研究过程可分为三步：1.在研究部件故障演化机理的基础上，以小波变换为手段对状态特征信号进行提取，建立具有独立性的特征向量集；2.面对样本数据多类别、线性不可分、不均匀分布等特点，建立基于数据的支持向量机预测模型；3.针对部件缓慢劣化和加剧劣化的情形，分别给出相应的视情维修和容错控制方案等安全对策。本项目的开展对提高我国高速轨道交通的安全性与可靠性具有十分重大的意义，同时对其它要求电力电子可靠运行的场合，也具有重要的参考价值和应用前景。

中文关键词： 机车牵引变流器；故障预警;诊断;识别；维修决策；容错控制；

英文摘要： As one complex nonlinear system, fault prediction and safety precautions of locomotive power converter are directly related to safe operation of the whole high-speed railway. This project investigates signal processing technology, fault prediction model and safety precautions. Based on historical and current data, as well as expert experiences, a data-based fault prediction theory and safety precautions of locomotive power converter are studied by using the approaches of fault prediction technique, wavelet transform, support vector machine and Markov decision. The research process can be divided into three steps: I. The state characteristic signals are extracted by using wavelet transform to set up the independent feature vector sets, on the basis of research on fault evolution mechanism of components, II. A data-based support vector machine prediction model is established in consideration of multi-class, non-linearly classification and non-uniform distribution characteristics of sampled data; III. Safety precautions including the corresponding condition-based maintenance and fault-tolerant control schemes are presented according to the moderative and aggravated degradations of components. The research of this project has great significance for improving the safety and reliability operation of high-speed railway

英文关键词： Locomotive Power Converter；Fault Prognosis; Detection and Isolation；Maintenance Decision；Tolerant Control；