电网技术Issue(5)：1272-1278,7.
基于决策树和支持向量机的电能质量扰动识别
Power Quality Disturbance Identification Using Decision Tree and Support Vector Machine
摘要
Abstract
A new approach to recognize power quality disturbances is proposed. Based on fast Fourier transform (FFT) combined with dynamic measure method three kinds of features in power quality disturbance signals are extracted and using S-transform four features in power quality disturbance signals are extracted, and by use of decision tree and support vector machine (SVM) a combination classifier is designed. Firstly, for disturbance types with evident harmonic frequencies in FFT spectrum the features of main frequency points in FFT spectrum are extracted by the extreme point-enveloped dynamic measure method, and combining with the features extracted by S-transform, the disturbance types are preliminarily classified into several categories, and then by use of the two features extracted by S-transform the follow-up classification can be implemented. During the classification of decision tree the SVM is used to distinguish voltage sag from voltage interruption, thus the trouble that the feature thresholds, which vary with signal-to- noise ratio (SNR), are hard to be determined can be overcome. Simulation experiments show that using the proposed method eleven power quality disturbance signals, including two kinds of compound disturbances, can be accurately recognized, and when SNR is lowered to 20 dB the recognition accuracy can still reach to 96.50%. Comparison of the obtained results with reported classification results shows that the proposed method is accurate, stable and can be utilized in environment of low SNR.关键词
电能质量/扰动识别/S变换/动态测度法/支持向量机/决策树Key words
power quality/disturbance recognition/S-transform, dynamic measure method/support vector machine/decision tree分类
信息技术与安全科学引用本文复制引用
陈华丰,张葛祥..基于决策树和支持向量机的电能质量扰动识别[J].电网技术,2013,(5):1272-1278,7.基金项目
国家自然科学基金项目(61170016)；教育部新世纪优秀人才支持计划项目(NCET-11-0715)及配套项目(SWJTU12CX008)；中央高校基本科研业务费专项资金项目(SWJTU11ZT07)。@@@@National Natural Science Foundation of China (61170016) （61170016）
Program for New Century Excellent Talents in University (NCET-11-0715) and SWJTU Supported Project(SWJTU12CX008) （NCET-11-0715）
Fundamental Research Funds for the Central Universities (SWJTU11ZT07) （SWJTU11ZT07）
