华东交通大学学报2018，Vol.35Issue(2)：129-136,8.
基于支持向量机的弓网间电弧诊断策略
Diagnosis Strategy for Arc State Between Catenary and Pantograph Based on Support Vector Machine
摘要
Abstract
The electric locomotive obtains the electric energy through the electrical contact between pantograph and catenary.And the arc fault between the pantograph and catenary is a common phenomenon when the electric locomotive is running. The arc fault in pantograph-catenary system will not only damage the catenary and the pantograph, but also disturb the operation of the electric equipment in electric locomotive. The arc fault has the characteristic of randomness and irregularity, so it is difficult to diagnose the fault timely and accurately. Ac-cording to the existing problems in arc fault diagnosis, this paper introduced a new diagnosis method based on the support vector machine(SVM).After obtaining the raw data of the current in pantograph-catenary system, the power spectrum entropy was adopted to extract the feature vectors needed by arc fault diagnosis and the SVM was used to classify these feature vectors. Then, the normal current from arc fault can be recognized. The re-search results show that the diagnosis model established in this paper has a high accuracy in classifying the fault state and normal state,which provides an useful method and research approach for arc fault diagnosis.关键词
弓网系统/功率谱熵/支持向量机/弓网间电弧Key words
pantograph-catenary system/power spectrum entropy/SVM/electric arc分类
交通工程引用本文复制引用
刘仕兵,曾聿田,刘欢,马志方..基于支持向量机的弓网间电弧诊断策略[J].华东交通大学学报,2018,35(2):129-136,8.基金项目
国家自然基金项目(11162006) （11162006）
江西省教育厅科技项目(GJJ150530) （GJJ150530）
江西省教育厅科技项目(GJJ160488) （GJJ160488）
