Features Selection for Partial Discharge and Interference Recognition of HV Cables based on Random Forest Method

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Paper number
1390
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
Authors
Wang, Ganjun, Zhongshan Power Supply Bureau of the Guangdong Power Grid Corporation- China Southern Power Grid Co.- Ltd., China
Li, Jingshu, Huazhong University of Science and Technology, China
Hu, Yufeng, China Southern Power Grid Co. Ltd., China
Peng, Xiaosheng, Huazhong University of Science and Technology, China
Wu, Yijiang, Zhongshan Power Supply Bureau of the Guangdong Power Grid Corporation China Southern Power Grid Co. Ltd., China
Chen, Yuzhu, Huazhong University of Science and Technology, China
Abstract
Optimal feature selection will contribute to the pattern recognition efficiency and accuracy of partial discharge (PD) signals by removing irrelevant and redundant PD features. Meanwhile, the effective new PD features, selected from a large amount of candidate features, could be applied to the PD based condition monitoring and diagnostic. A novel Random Forest (RF) algorithm based PD feature selection method is presented in the paper. Firstly, the flowchart of RF-based optimal PD feature selection for HV cables and the feature importance measurement of RF method were introduced. Secondly, based on the 5 types of artificial defects of ethylene-propylene (EPR) cables, PD data acquisition and feature extraction were carried out. Subsequently, the RF-based feature selection was applied to the laboratory PD data and was evaluated by the visualization analysis of several top features. The results show that the features which could describe the "fast pulses" and "slow pulses" are effective for PD and interference identification. The wavelet combination features are evaluated to be effective for the recognition of different types of PD signals. RF method is an effective way for PD feature selection, which could potentially be applied to feature selection of other HV apparatus.
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/395
http://dx.doi.org/10.34890/621
ISSN
2032-9644
ISBN
978-2-9602415-0-1