Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms

Accurate recognition of distribution line fault types can provide directional guidance for line operation and maintenance personnel. Based on the analysis of time-frequency features of fault waveform, a recognized method of distribution line fault type was proposed in this paper. Through modeling an...

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Main Authors: Xue Qin, Peng Wang, Yadong Liu, Linhui Guo, Gehao Sheng, Xiuchen Jiang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8019788/
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spelling doaj-15b9c095f2d34bff89a46f25ee6cf6682021-03-29T20:38:56ZengIEEEIEEE Access2169-35362018-01-0167291730010.1109/ACCESS.2017.27280158019788Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault WaveformsXue Qin0https://orcid.org/0000-0002-1577-5963Peng Wang1Yadong Liu2https://orcid.org/0000-0002-7921-6757Linhui Guo3Gehao Sheng4Xiuchen Jiang5Department of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong Unversity, Shanghai, ChinaState Grid, Electric Power Research Institute of Electric Power of Henan, Zhengzhou, ChinaDepartment of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong Unversity, Shanghai, ChinaDepartment of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong Unversity, Shanghai, ChinaDepartment of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong Unversity, Shanghai, ChinaDepartment of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiaotong Unversity, Shanghai, ChinaAccurate recognition of distribution line fault types can provide directional guidance for line operation and maintenance personnel. Based on the analysis of time-frequency features of fault waveform, a recognized method of distribution line fault type was proposed in this paper. Through modeling and theoretical analysis of waveforms of different fault types, characteristic parameters, which could characterize waveforms of different fault types from three aspects, time domain, frequency domain, and electric arc, were put forward. Calculation formula for extracting characteristic parameters according to fault waveform data was proposed, recognition logic was established by taking multi-parameter fusion as a basis, and then,automatic recognition of distribution line fault types caused by different factors was realized through detection and classification of characteristic parameters of input waveform data. Finally, 136 groups of field fault waveform data provided by the Electric Power Research Institute were used to do closed-loop control and verification of the algorithm, and results indicated that recognition success rate reached 90%, which verified the feasibility of using time-frequency characteristics of fault waveform to realize recognition of distribution line fault types.https://ieeexplore.ieee.org/document/8019788/Distribution linefault causetime-frequency characteristicselectric arc modelrecognition logic
collection DOAJ
language English
format Article
sources DOAJ
author Xue Qin
Peng Wang
Yadong Liu
Linhui Guo
Gehao Sheng
Xiuchen Jiang
spellingShingle Xue Qin
Peng Wang
Yadong Liu
Linhui Guo
Gehao Sheng
Xiuchen Jiang
Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
IEEE Access
Distribution line
fault cause
time-frequency characteristics
electric arc model
recognition logic
author_facet Xue Qin
Peng Wang
Yadong Liu
Linhui Guo
Gehao Sheng
Xiuchen Jiang
author_sort Xue Qin
title Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
title_short Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
title_full Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
title_fullStr Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
title_full_unstemmed Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
title_sort research on distribution network fault recognition method based on time-frequency characteristics of fault waveforms
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description Accurate recognition of distribution line fault types can provide directional guidance for line operation and maintenance personnel. Based on the analysis of time-frequency features of fault waveform, a recognized method of distribution line fault type was proposed in this paper. Through modeling and theoretical analysis of waveforms of different fault types, characteristic parameters, which could characterize waveforms of different fault types from three aspects, time domain, frequency domain, and electric arc, were put forward. Calculation formula for extracting characteristic parameters according to fault waveform data was proposed, recognition logic was established by taking multi-parameter fusion as a basis, and then,automatic recognition of distribution line fault types caused by different factors was realized through detection and classification of characteristic parameters of input waveform data. Finally, 136 groups of field fault waveform data provided by the Electric Power Research Institute were used to do closed-loop control and verification of the algorithm, and results indicated that recognition success rate reached 90%, which verified the feasibility of using time-frequency characteristics of fault waveform to realize recognition of distribution line fault types.
topic Distribution line
fault cause
time-frequency characteristics
electric arc model
recognition logic
url https://ieeexplore.ieee.org/document/8019788/
work_keys_str_mv AT xueqin researchondistributionnetworkfaultrecognitionmethodbasedontimefrequencycharacteristicsoffaultwaveforms
AT pengwang researchondistributionnetworkfaultrecognitionmethodbasedontimefrequencycharacteristicsoffaultwaveforms
AT yadongliu researchondistributionnetworkfaultrecognitionmethodbasedontimefrequencycharacteristicsoffaultwaveforms
AT linhuiguo researchondistributionnetworkfaultrecognitionmethodbasedontimefrequencycharacteristicsoffaultwaveforms
AT gehaosheng researchondistributionnetworkfaultrecognitionmethodbasedontimefrequencycharacteristicsoffaultwaveforms
AT xiuchenjiang researchondistributionnetworkfaultrecognitionmethodbasedontimefrequencycharacteristicsoffaultwaveforms
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