基于蝙蝠算法优化最小二乘双支持向量机的变压器故障诊断
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摘要
变压器故障诊断是确保电力系统安全运行的重要技术手段,为了提高变压器的故障诊断精度,提出一种基于蝙蝠算法优化最小二乘双支持向量机的变压器故障诊断方法。针对变压器故障诊断过程中的多分类问题,为了减小误差积累、提高精度,文中根据类间相异度矩阵构建哈夫曼树,然后建立基于最小二乘双支持向量机的多类分类故障诊断模型,并采用蝙蝠算法对模型中的每一个两分类器的参数进行优化。仿真实例表明,与其他方法相比较,该方法可以获得更高的故障诊断精度。
Transformer fault diagnosis is an important technical means to ensure the safety operation of power system.In order to improve the accuracy of fault diagnosis of transformer,this paper proposes a fault diagnosis method of transformer which is based on LSTSVM optimized by bat algorithm. For the multiple classification problem of transformer fault diagnosis,in order to reduce the accumulation of errors and improve the accuracy,a Huffman tree is built according to dissimilarity matrix between classes,and then,we established a multi-classification fault diagnosis model based on LSTSVM. And parameter of each classifier in the model is optimized by bat algorithm. The simulation results show that the method in this paper can achieve higher accuracy compared to other method.
Transformer fault diagnosis is an important technical means to ensure the safety operation of power system.In order to improve the accuracy of fault diagnosis of transformer,this paper proposes a fault diagnosis method of transformer which is based on LSTSVM optimized by bat algorithm. For the multiple classification problem of transformer fault diagnosis,in order to reduce the accumulation of errors and improve the accuracy,a Huffman tree is built according to dissimilarity matrix between classes,and then,we established a multi-classification fault diagnosis model based on LSTSVM. And parameter of each classifier in the model is optimized by bat algorithm. The simulation results show that the method in this paper can achieve higher accuracy compared to other method.
引文
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[19]D.A.Huffman.A method for the construction of minimum-redundancy codes,in:Proceedings of The I.R.E,1951,(40):1098-1101.
[20]Wang Deyan,Xiao Ying.Huffman tree optimization particle swarm optimization.Proceedings-2012 International Conference on Intelligent Systems Design and Engineering Applications[J].ISDEA,2012:286-288.
[21]Yang Xin She.A new metaheuristic;bat}nspired algorithm[C].Nature Inspired Cooperative Strategies for Optimization[J].Berlin Heidelberg:Springer Berlin Heidelberg,2010,284:65-74.
[22]费胜巍,苗玉彬,刘成良,等.基于粒子群优化支持向量机的变压器故障诊断[J].高电压技术,2009,35(3):509-513.Fei Shengwei,Miao Yubin,Liu Chengliang,et al.Fault Diagnosis of Transformer Based on Particle Swarm Optimization-based Support Vector Machine[J].High Voltage Engineering,2009,35(3):509-513.
[2]操敦奎.变压器油中气体分析诊断与故障检查[M].北京:中国电力出版社,2005:95-99.
[3]禹建丽,卞帅.基于BP神经网络的变压器故障诊断模型[J].系统仿真学报,2014,26(6):1343-1349.Yu Jianli,Bian Shuai.Fault Diagnosis Model of Transformer Based on BP Neural Network[J].Journal of System Simulation,2014,26(6):1343-1349.
[4]程声烽,程小华,杨露.基于改进粒子群算法的小波神经网络在变压器故障诊断中的应用[J].电力系统保护与控制,2014,42(19):37-42.Cheng Shengfeng,Cheng Xiaohua,Yang Lu.Application of wavelet neural network with improved particle swarm optimization algorithm in power transformer fault diagnosis[J].Power System Protection and Control,2014,42(19):37-42.
[5]Yang,Zhiqiang.Power transformer fault diagnosis based on the SOM network combined with the BP neural network[J].Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia,2016,39(3):319-326.
[6]郑含博,王伟,李晓纲,等.基于多分类最小二乘支持向量机和改进粒子群优化算法的电力变压器故障诊断方法[J].高电压技术,2014,40(11):3424-3429.Zheng Hanbo,Wang Wei,Li Xiaogang,et al.Fault Diagnosis Method of Power Transformers Using Multi-class LS-SVM and Improved PSO[J].High Voltage Engineering,2014,40(11):3424-3429.
[7]朱永利,尹金良.组合核相关向量机在电力变压器故障诊断中的应用研究[J].中国电机工程学报,2013,33(22):12,68-74.Zhu Yongli,Yin Jinliang.Study on Application of Multi-kernel Learning Relevance Vector Machines in Fault Diagnosis of Power Transformers[J].Transactions of China Electrotechnical Society,2013,33(22):12,68-74.
[8]Li H Z,Chen S X,Qian T,Tang W H,Wu Q H.Power transformer fault classification by combining genetic reduction with optimized multilayer support vector machine[J].Proceedings of the 2015 IEEE Innovative Smart Grid Technologies-Asia,ISGT ASIA 2015,January19,2016.
[9]Li Jinzhong,Zhang,Qiaogen,Wang Ke,Wang Jianyi,Zhou Tianchun,Zhang Yiyi.Optimal dissolved gas ratios selected by genetic algorithm for power transformer fault diagnosis based on support vector machine[J].IEEE Transactions on Dielectrics and Electrical Insulation,2016,23(2):1198-1206.
[10]白翠粉,高文胜,金雷,等.基于3层贝叶斯网络的变压器综合故障诊断[J].高电压技术,2013,39(2):330-335.Bai Cuifen,Gao Wenshen,Jin Lei,et al.Integrated Disgnosis of Transformer Faults Based on Three-layer Bayesian Network[J].High Voltage Engineering,2013,39(2):330-335.
[11]赵文清.基于选择性贝叶斯分类器的变压器故障诊断[J].电力自动化设备,2011,31(2):44-47.Zhao Wenqing.Transformer fault diagnosis based on selective Bayes classifier[J].Electric Power Automation Equipment,2011,31(2):44-47.
[12]郑元兵,孙才新,李剑,等.变压器故障特征量可信度的关联规则分析[J].高电压技术,2012,38(1):82-88.Zheng Yuanbing,Sun Caixin,Li Jian,et al.Association Rule Analysis on Confidence of Features for Transformer Faults[J].High Voltage Engineering,2012,38(1):82-88.
[13]杜文霞,句希源,吕锋.基于模糊聚类算法的变压器故障诊断研究[J].变压器,2009,46(8):65-69.Du Wenxia,Ju Xiyuan,Lv Feng.Research on Transformer Fault Diagnosis Based on Fuzzy Clustering Algorithm[J].Transformer,2009,46(8):65-69.
[14]周湶,王时征,廖瑞金,等.基于Ada Boost优化云理论的变压器故障诊断方法[J].高电压技术,2015,41(11):3804-3811.Zhou Quan,Wang Shizheng,Liao Ruijin,et al.Power Transformer Fault Diagnosis Method Based on Cloud Model of Ada Boost Algorithm[J].High Voltage Engineering,2015,41(11):3804-3811.
[15]R.Khemchandani,S.Chandra,et al.Twin support vector machines for pattern classification[J].IEEE Trans.Pattern Anal.Mach.Intell,2007,29(5):905-910.
[16]Nasiri J A,Charkari N M,Mozafari K.Energy-based model of least squares twin Support Vector Machines for human action recognition[J].Signal Processing,2014,104(6):248-257.
[17]Ye Qiaolin,Zhao Chunxia,Ye Ning.Least squares twin support vector machine elassifieatien via maximum one-class within class variance[J].Optimization Methods&Software,2012,27(1):53-69.
[18]M.A.Kumar,M.Gopal.Least squares twin support vector machines for pattern classification[J].Expert Systems with Applications.2009,36(4):7535-7543.
[19]D.A.Huffman.A method for the construction of minimum-redundancy codes,in:Proceedings of The I.R.E,1951,(40):1098-1101.
[20]Wang Deyan,Xiao Ying.Huffman tree optimization particle swarm optimization.Proceedings-2012 International Conference on Intelligent Systems Design and Engineering Applications[J].ISDEA,2012:286-288.
[21]Yang Xin She.A new metaheuristic;bat}nspired algorithm[C].Nature Inspired Cooperative Strategies for Optimization[J].Berlin Heidelberg:Springer Berlin Heidelberg,2010,284:65-74.
[22]费胜巍,苗玉彬,刘成良,等.基于粒子群优化支持向量机的变压器故障诊断[J].高电压技术,2009,35(3):509-513.Fei Shengwei,Miao Yubin,Liu Chengliang,et al.Fault Diagnosis of Transformer Based on Particle Swarm Optimization-based Support Vector Machine[J].High Voltage Engineering,2009,35(3):509-513.