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基于数学形态学与动态时间扭曲的电压扰动分类

赵静 何正友 王丽霞 钱清泉

赵静, 何正友, 王丽霞, 钱清泉. 基于数学形态学与动态时间扭曲的电压扰动分类[J]. 西南交通大学学报, 2009, 22(2): 208-214.
引用本文: 赵静, 何正友, 王丽霞, 钱清泉. 基于数学形态学与动态时间扭曲的电压扰动分类[J]. 西南交通大学学报, 2009, 22(2): 208-214.
ZHAO Jing, HE Zhengyou, WANG Lixia, QIAN Qingquan. Classification of Voltage Disturbances Based on Mathematical Morphology and Dynamic Time Warping[J]. Journal of Southwest Jiaotong University, 2009, 22(2): 208-214.
Citation: ZHAO Jing, HE Zhengyou, WANG Lixia, QIAN Qingquan. Classification of Voltage Disturbances Based on Mathematical Morphology and Dynamic Time Warping[J]. Journal of Southwest Jiaotong University, 2009, 22(2): 208-214.

基于数学形态学与动态时间扭曲的电压扰动分类

基金项目: 

国家自然科学基金资助项目(50877068)

四川省杰出青年基金资助项目(No.06ZQ026-012)

教育部优秀新世纪人才支持计划项目(NCET-06-0799)

详细信息
    作者简介:

    赵静(1982- ),女,博士研究生,研究方向为电能质量扰动信号的分析与识别,E-mail:carolzj1123@hotmail.com.

    通讯作者:

    何正友(1970- ),男,教授,研究方向为信息理论在电力系统中的应用, E-mail: hezy@home.swjtu.edu.cn

Classification of Voltage Disturbances Based on Mathematical Morphology and Dynamic Time Warping

  • 摘要: 为提高电压扰动信号分类识别的精度,提出了一种基于数学形态学与动态时间扭曲的新算法.该算法首先通过形态滤波器对信号进行滤波处理,然后利用dq变换提取滤波输出的特征,再通过动态时间扭曲分类器与参考模板进行匹配,最后获得有效的分类识别结果.用Matlab进行仿真分析的结果表明,该算法能有效识别各类扰动信号,准确率高,即使在强噪声环境下,识别精度也超过84%.

     

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出版历程
  • 收稿日期:  2007-11-27
  • 刊出日期:  2009-04-20

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