电测与仪表Issue(4)：22-26,5.
基于支持向量机的低压串联故障电弧识别方法研究*
Series Arc Fault Recognition Method Based on Support Vector Machine Approach
摘要
Abstract
When arc fault occurs in the circuit the traditional circuit interrupters cannot detect series arc fault because of the low current value. This paper introduces a new recognition method of series arc fault which is based on Support Vector Machine (SVM) to solve this problem. First, current data of different kinds of loads are collected by a self-made arc generator, based on which, an arc fault SVM classifier is trained, the accuracy of which is then tested by experiments carried out in linear and non-linear loads circuits collectively. It turns out that the SVM approach is an effective way to distinguish the series arc fault with the highest accuracy of 96%. The SVM approach is useful to detect arc fault with a high efficiency and low requirement of hardware, meanwhile it can also save and process the current waveforms.关键词
低压串联故障电弧/支持向量机/分类辨识/电气火灾Key words
low voltage series arc fault/Support Vector Machine(SVM)/classification recognition/electrical fire accidents分类
信息技术与安全科学引用本文复制引用
王子骏,张峰,张士文,顾昊英,曹潘亮..基于支持向量机的低压串联故障电弧识别方法研究*[J].电测与仪表,2013,(4):22-26,5.基金项目
上海市“科技创新行动计划”2009年度社会发展领域重点科技资助项目 （）
