常炳双,赵治月

• 1:沧州师范学院机械与电气工程学院
• 2:天津大学

摘要(Abstract)：

为了提高电能质量扰动识别的准确性,针对当前电能质量扰动识别存在精度低、误差大等难题,提出小波包和最小二乘支持向量机的电能质量扰动识别模型(WP-LSSVM)。首先对当前电能质量扰动识别研究现状进行分析,并采用小波包提取电能质量扰动特征向量;然后采用最小二乘支持向量机建立电能质量扰动识别的分类器;最后通过电能质量扰动识别仿真实验验证其有效性。结果表明,WP-LSSVM可以很好地区别电能质量扰动类别,提高了电能质量扰动识别正确率,而且误识率要远远低于其他电能质量扰动识别模型,具有十分显著的优越性。

关键词(KeyWords)： 电能质量;扰动识别;特征向量;分类器;支持向量机;最小二乘

Abstract:

Keywords:

基金项目(Foundation): 2015年河北省教育厅科研项目:焊接缺陷电涡流检测技术研究(QN2016321)~~

作者(Author): 常炳双,赵治月

DOI: 10.16652/j.issn.1004-373x.2018.03.039

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