• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus 收录
  • 全国中文核心期刊
  • 中国科技论文统计源期刊
  • 中国科学引文数据库来源期刊

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%.

     

  • 李天云,赵研,李楠,等.基于HHT的电能质量检测新方法[J].中国电机工程学报,2005,25(17):52-56.LI Tianyun,ZHAO Yan,LI Nan,et al.A new method for power quality detection based on HHT[J].Proceedings of the CSEE,2005,25(17):52-56.[2] 赵凤展,杨仁刚.基于短时傅里叶变换的电压暂降扰动检测[J].中国电机工程学报,2007,27(10):28-34,109.ZHAO Fengzhan,YANG Rengang.Voltage sag disturbance detection based on short time Fourier transform[J].Proceedings of the CSEE,2007,27(10):28-34,109.[3] 陈祥训.采用小波技术的几种电能质量扰动的测量与分类方法[J].中国电机工程学报,2002,22(10):1-6.CHEN Xiangxun.Wavelet-based measurements and classification of short duration power quality disturbances[J].Proceedings of the CSEE,2002,22(10):1-6.[4] 占勇,程浩忠,丁屹峰,等.基于S变换的电能质量扰动支持向量机分类识别[J].中国电机工程学报,2005,25(4):51-56.ZHAN Yong,CHENG Haozhong,DING Yifeng,et al.S-transform-based classification of power quality disturbance signals by support vector machines[J].Proceedings of the CSEE,2005,25(4):51-56.[5] 李庚银,罗艳,周明,等.基于数学形态学和网格分形的电能质量扰动检测及定位[J].中国电机工程学报,2006,26(3):25-30.LI Gengyin,LUO Yan,ZHOU Ming,et al.Power quality disturbance detection and location based on mathematical morphology and grille fractal[J].Proceedings of the CSEE,2006,26(3):25-30.[6] 石敏,吴正国,徐袭.基于概率神经网络和双小波的电能质量扰动自动识别[J].电力自动化设备,2006,26(3):5-8.SHI Min,WU Zhengguo,XU Xi.Auto recognition of power quality disturbance based on probabilistic neural networks and double wavelet[J].Electric Power Automation Equipment,2006,26(3):5-8.[7] 李智勇,吴为麟,林震宇.基于相空间重构和支持向量机的电能扰动分类方法[J].电力系统自动化,2007,31(5):70-75.LI Zhiyong,WU Weilin,LIN Zhenyu.A power disturbance classification method based on phase space reconstruction and support vector machines[J].Automation of Electric Power System,2007,31(5):70-75.[8] 何为,杨洪耕.基于第二代小波变换和离散隐马尔可夫模型的电能质量扰动分类[J].电工技术学报,2007,22(5):146-152.HE Wei,YANG Honggeng.Disturbance classification based on second generation wavelet transform and discrete hidden Markov models[J].Trans.of China Electrotechnical Society,2007,22(5):146-152.[9] 徐袭,石敏.一种基于粗糙集与小波变换的电能质量分类方法[J].电力自动化设备,2005,25(11):15-18.XU Xi,SHI Min.Power quality classification based on rough set and wavelet transform[J].Electric Power Automation Equipment,2005,25(11):15-18.[10] VUORI V,LAAKSONEN J,KANGAS J.Influence of erroneous learning samples on adaptation in on-line handwriting recognition[J].Pattern Recognition,2002,35(4):915-925.[11] SERRA J.Morphological filtering:an overview[J].Signal Processing,1994,38(4):3-11.[12] 欧阳森,王建华,宋政湘,等.基于数学形态学的电力系统采样数据处理方法[J].电网技术,2003,27(9):61-65.OUYANG Sen,WANG Jianhua,SONG Zhengxiang,et al.A new power system sampled data processing method based on morphology theory[J].Power System Technology,2003,27(9):61-65.[13] 曾纪勇.基于数学形态学的电能质量检测方法及应用[D].武汉:华中科技大学,2005.[14] 吴军基,吴伊昂,贺济峰,等.数学形态学在行波滤波中的应用[J].继电器,2005,17(33):21-26.WU Junji,WU Yiang,HE Jifeng,et al.Application of mathematical morphology in transmission line fault location[J].Relay,2005,17(33):21-26.[15] 曾纪勇,丁洪发,段献忠.基于数学形态学的谐波检测与电能质量扰动定位方法[J].中国电机工程学报,2005,25(21):57-61.ZENG Jiyong,DING Hongfa,DUAN Xianzhong.Harmonics detection and disturbance location methods based on mathematical morphology[J].Proceedings of the CSEE,2005,25(21):57-61.[16] 翁颖钧,朱仲英.基于动态时间弯曲的时序数据聚类算法的研究[J].计算机仿真,2004,(21)3:37-40,144.WENG Yingjun,ZHU Zhongying.Novel algorithm for time series data mining based on dynamic time warping[J].Computer Simulation,2004,3(21):37-40,144.[17] 王振浩,杜凌艳,李国庆,等.动态时间规整算法诊断高压断路器故障[J].高电压技术,2006,32(10):36-38.WANG Zhenhao,DU Lingyan,LI Guoqing,et al.Fault diagnosis of high voltage circuit breakers based on dynamic time warping algorithm[J].High Voltage Engineering,2006,32(10):36-38.[18] 徐波,唐海龙,李行善.基于DTW的涡扇发动机气路故障定量诊断方法[J].北京航空航天大学学报,2004,30(6):524-528.XU Bo,TANG Hailong,LI Xingshan.DTW based quantitative fault diagnosis of gas path component in turbofan[J].Journal of Beijing University of Aeronautics and Astronautics,2004,30(6):524-528.[19] 徐波,于劲松,李行善.基于路径约束的动态时间规整方法研究[J].系统工程与电子技术,2004,26(1):103-105.XU Bo,YU Jinsong,LI Xingshan.Research of dynamic time warping approach based on path constraint[J].Systems Engineering and Electronic,2004,26(1):103-105.[20] YOUSSEF A M,ABDEL-GALIL T K,El-SAADANY E F,et al.Disturbance classification utilizing dynamic time warping classifier[J].IEEE Trans.on Power Delivery,2004,1(19):272-278.
  • 加载中
计量
  • 文章访问数:  1698
  • HTML全文浏览量:  50
  • PDF下载量:  489
  • 被引次数: 0
出版历程
  • 收稿日期:  2007-11-27
  • 刊出日期:  2009-04-20

目录

    /

    返回文章
    返回