引用本文:方 科,黄元亮,刘新东.基于自适应PSO算法的LS SVM牵引变压器绝缘故障诊断模型[J].电力自动化设备,2011,31(3):
FANG Ke,HUANG Yuanliang,LIU Xindong.Insulation fault diagnosis model based on adaptive PSO and LS-SVM for traction transformer[J].Electric Power Automation Equipment,2011,31(3):
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基于自适应PSO算法的LS SVM牵引变压器绝缘故障诊断模型
方 科, 黄元亮, 刘新东
暨南大学 电气自动化研究所,广东 珠海 519070
摘要:
结合罗杰斯比值法,基于自适应PSO算法和最小二乘支持向量机(LS-SVM),提出一种牵引变压器绝缘故障诊断模型。该模型提出一种自适应PSO算法,即根据群体的收敛程度和个体的适应值来调整惯性权重,加快训练速度,利用该算法迭代求解LS-SVM中出现的矩阵方程,避免矩阵求逆,节省内存;为了快速和准确地区分牵引变压器12种绝缘故障,该模型构建12个自适应PSO的LS-SVM分类器。通过对600组牵引变压器的故障数据的处理表明,所提出的基于自适应PSO优化的LS-SVM算法优于经典SVM算法和标准PSO的LS-SVM算法,收敛速度快,识别精度高。
关键词:  故障诊断  牵引变压器  最小二乘支持向量机  粒子群优化  罗杰斯比值法  多分类
DOI:
分类号:
基金项目:国家自然科学基金项目(51007030);铁道部科技研究开发计划课题(2008J002)
Insulation fault diagnosis model based on adaptive PSO and LS-SVM for traction transformer
FANG Ke, HUANG Yuanliang, LIU Xindong
Electric Automation Institute of Jinan University,Zhuhai 519070,China
Abstract:
Combined with the Rogers ratio method,an insulation fault diagnosis model based on adaptive PSO and LS-SVM is presented for traction transformer. It adjusts the inertia weights to accelerate the training speed according to the swarm convergence and individual fitness. The matrix of LS-SVM is solved through the adaptive PSO to avoid the inverse solution for memory saving. In order to quickly and accurately distinguish 12 insulation faults,12 LS-SVM classifiers based on adaptive PSO are built. Tests on 600 groups of fault data indicate that,the proposed model has faster convergence velocity and higher accuracy than classical SVM model and LS-SVM model based on standard PSO.
Key words:  fault diagnosis  traction transformer  least squares support vector machine  particle swarm optimization  Rogers ratio method  multi-classification

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