| 基于S变换和最小二乘支持向量机的电能质量扰动识别 |
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| 引用本文： | 王学伟,张宏财.基于S变换和最小二乘支持向量机的电能质量扰动识别[J].电测与仪表,2009,46(8). |
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| 作者姓名： | 王学伟 张宏财 |
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| 作者单位： | 北京化工大学,信息科学与技术学院,北京,100029 |
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| 摘 要： | 采用S变换和最小二乘支持向量机相结合,构建了一种电能质量扰动识别的新方法.首先利用S变换对电能质量扰动信号进行时频分解;然后,从扰动信号S变换的结果中,提取扰动信号的特征向量,组成训练样本和测试样本;最后,使用最小输出编码的最小二乘支持向量机对扰动信号进行训练,实现电能质量扰动信号自动分类和识别.仿真结果表明,该方法识别准确率高,抗噪能力强,且训练时间很短,适用于电能质量扰动辨识系统.
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| 关 键 词： | 电能质量 扰动识别 S变换 最小二乘支持向量机 |
Power Quality Disturbances Identification Based on S-Transform and LS-SVM |
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| WANG Xue-wei,ZHANG Hong-cai.Power Quality Disturbances Identification Based on S-Transform and LS-SVM[J].Electrical Measurement & Instrumentation,2009,46(8). |
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| Authors: | WANG Xue-wei ZHANG Hong-cai |
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| Affiliation: | WANG Xue-wei,ZHANG Hong-cai(College of Information Science , Technology,Beijing University of Chemical Technology,Beijing 100029,China) |
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| Abstract: | A new method based on S-transform time-frequency analysis and least square support vector machine(LS-SVM) is presented for power quality(PQ) disturbances identification.Firstly using S-transform analyzes PQ disturbances.Then feature components were extracted from the detecting outputs for training.Finally LS-SVM based on minimum output coding is used to classify and identify PQ disturbances.Simulation results indicate that the proposed method has an excellent performance on correct ratio and training speed,... |
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| Keywords: | power quality disturbances identification S-transform least square support vector machine |
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