电力系统保护与控制Issue(8)：8-13,6.
基于布谷鸟算法和支持向量机的变压器故障诊断
Fault diagnosis of transformer based on the cuckoo search and support vector machine
薛浩然 1张珂珩 2李斌 1彭晨辉2
作者信息
- 1. 国网电力科学研究院/南京南瑞集团公司，江苏 南京 210003
- 2. 江苏瑞中数据 股份有限公司，江苏 南京 210003
- 折叠
摘要
Abstract
Power transformer is one of the important equipment in power system operation, correct diagnosis of the fault and defects is related to the safe operation of the entire grid. Support vector machine(SVM) can better solve the multi-classification with small sample and nonlinear characteristics, it is suitable for fault diagnosis of transformer. In this paper, we get the best global optimal solution of SVM using the cuckoo search algorithm, and get the SVM classification model with the best parameters. In this classification model, the relative content of each gas of dissolved gas analysis (DGA) is put as the evaluation indexes. The transformer fault is divided into 4 types of fault, i.e. low energy discharge, high energy discharge, mid-low temperature overheating, and high temperature overheating. Through the analysis of the existing data instance, the accuracy of the classification model using cuckoo search algorithm is better than that using grid search (GS), particle swarm optimization (PSO) and genetic algorithm (GA).关键词
支持向量机/布谷鸟算法/变压器/故障诊断/分类模型Key words
support vector machine (SVM)/cuckoo search/transformer/fault diagnosis/classification model分类
信息技术与安全科学引用本文复制引用
薛浩然,张珂珩,李斌,彭晨辉..基于布谷鸟算法和支持向量机的变压器故障诊断[J].电力系统保护与控制,2015,(8):8-13,6.
