PD Pattern Recognition Using Complex Wavelet Transform Coefficient As The Feature
CSTR:
Author:
Affiliation:

Clc Number:

TM835

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Complex wavelet transform can characterize the partial feature of the PD signal in time-domain and frequency-domain,and provides the unique phasic information.In this paper,the PD pulse waveforms which are created by 4 typical insulated defects are transformed by complex wavelet,and then the complex wavelet coefficient's real part,imaginary part and compound coefficient are clustered by the Fuzzy c-means,the energy of the cluster is the feature of pattern recognition.Discharge samples are got through large number of experiments,and BPNN can identify the PD created by 4 typical insulated defects effectively.The results show that the feature extracted from compound coefficient is better than the feature extracted form the real part and imaginary part of complex wavelet coefficient or wavelet coefficient.

    Reference
    Related
    Cited by
Get Citation

唐炬,高丽,唐铭,张晓星,周倩.以复小波变换系数为特征量的局放模式识别[J].重庆大学学报,2007,30(4):21~

Copy
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:December 07,2006
  • Adopted:
  • Online:
  • Published:
Article QR Code