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小波多尺度信息综合的行波波头检测算法研究
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  • 英文篇名:Traveling Wave Head Detection Algorithm Based on Wavelet Multiscale Information Fusion
  • 作者:郑楚韬 ; 孔祥轩 ; 关家华 ; 谭家琪 ; 陆凯烨 ; 王伟冠 ; 游金梁 ; 林刚 ; 张朕
  • 英文作者:ZHENG Chutao;KONG Xiangxuan;GUAN Jiahua;TAN Jiaqi;LU Kaiye;WANG Weiguan;YOU Jinliang;LIN Gang;ZHANG Zhen;Guangdong Foshan Power Supply Bureau;School of Electrical and Engineering,Wuhan University;
  • 关键词:行波波头 ; 卷积神经网络 ; 小波变换 ; 平行坐标系
  • 英文关键词:traveling wave head;;CNN;;wavelet transform;;parallel coordinates
  • 中文刊名:XBDJ
  • 英文刊名:Smart Power
  • 机构:广东电网有限责任公司佛山供电局;武汉大学电气与自动化学院;
  • 出版日期:2019-05-20
  • 出版单位:智慧电力
  • 年:2019
  • 期:v.47;No.307
  • 基金:国家自然科学基金资助项目(51777142)~~
  • 语种:中文;
  • 页:XBDJ201905016
  • 页数:6
  • CN:05
  • ISSN:61-1512/TM
  • 分类号:103-108
摘要
提出了一种小波变换多尺度信息综合的行波波头检测算法,首先利用小波变换的多尺度分析对故障行波信号进行处理,得到各个尺度下的小波系数模极大值,然后将模极大值依次标定在平行坐标系下并形成灰度图片,最后利用卷积神经网络搭建波头检测模型。本算法利用平行坐标系巧妙的将小波变换与CNN相联系,结合了小波变换多尺度下的信息,为行波波头的检测提供了一种新思路。
        The key to traveling wave protection and ranging technology lies in the detection of fault wave heads, which is also the focus of research. Wavelet multi-scale information fusion based traveling wave detection algorithm is proposed. Firstly, the wavelet signal is processed by multi-scale analysis of wavelet transform to get the modular maxima at each scale. Then the modular maxima are calibrated in parallel coordinate system and gray scale images are formed. Finally, a wave head detection model is constructed using convolutional neural network. This algorithm uses the parallel coordinate system to intelligently associate the wavelet transform with CNN,which provides a new idea for the detection of traveling wave heads.
引文
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