A Novel Partial Discharge Detection Algorithm in Power Transmission Lines Based on Deep Learning

被引:2
|
作者
Ding, Benxiang [1 ]
Zhu, Hongwei [1 ]
机构
[1] Zhejiang Univ, Inst VLSI design, Hangzhou, Peoples R China
关键词
power transmission line; partial discharge; fault detection; deep learning; LSTM; textCNN;
D O I
10.1109/SPIES52282.2021.9633848
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The insulation condition of the power transmission line directly affects whether the power system can operate safely. Partial discharge (PD) is one of the main reasons for the deterioration of power line insulation. Therefore, the partial discharge detection of power transmission lines is of great significance. However, partial discharge detection is not easy to achieve for many other sources of noise could be falsely attributed to PD. Here we propose a novel altorithm based on deep learning model. We make an attempt to combine LSTM with textCNN to improve the performance of partial discharge detection. The algorithm mainly includes signal denoising processing, feature extraction, and then inferring whether there is a partial discharge phenomenon in the circuit through a deep learning model. Experimental results show that the proposed method can effectively detect partial discharges and has excellent performance.
引用
收藏
页码:100 / 104
页数:5
相关论文
共 50 条
  • [1] Interpretable Detection of Partial Discharge in Power Lines with Deep Learning
    Michau, Gabriel
    Hsu, Chi-Ching
    Fink, Olga
    SENSORS, 2021, 21 (06) : 1 - 14
  • [2] Deep learning based insulator fault detection algorithm for power transmission lines
    Wang, Han
    Yang, Qing
    Zhang, Binlin
    Gao, Dexin
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2024, 21 (04)
  • [3] Automatic Power Transmission Towers Detection Based on the Deep Learning Algorithm
    Mo, Yifu
    Xie, Ruibiao
    Pan, Qishen
    Zhang, Baoxing
    2021 2ND INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND INTELLIGENT CONTROL (ICCEIC 2021), 2021, : 11 - 15
  • [4] Partial discharge detection in power lines using automated machine learning
    Rivas, Jannery
    Boya-Lara, Carlos
    Poveda, Hector
    2022 8TH INTERNATIONAL ENGINEERING, SCIENCES AND TECHNOLOGY CONFERENCE, IESTEC, 2022, : 223 - 230
  • [5] Bolt Detection Technology of Transmission Lines Based on Deep Learning
    Zhang S.
    Wang H.
    Dong X.
    Li Y.
    Li Y.
    Wang X.
    Sun Y.
    Dianwang Jishu/Power System Technology, 2021, 45 (07): : 2821 - 2828
  • [6] Detection of partial discharge patterns in hybrid high voltage power transmission lines based on parallel recognition method
    Yang Y.
    Wu Y.
    Gao Y.
    Huang Y.
    Liu S.
    Wang Y.
    PeerJ Computer Science, 2024, 10
  • [7] Detection of partial discharge patterns in hybrid high voltage power transmission lines based on parallel recognition method
    Yang, Yang
    Wu, Yongye
    Gao, Yifei
    Huang, Yixuan
    Liu, Shukun
    Wang, Yuanshi
    PEERJ COMPUTER SCIENCE, 2024, 10
  • [8] Component identification and defect detection in transmission lines based on deep learning
    Zheng, Xiangyu
    Jia, Rong
    Aisikaer
    Gong, Linling
    Zhang, Guangru
    Dang, Jian
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 40 (02) : 3147 - 3158
  • [9] Obstacle Detection for Power Transmission Line Based on Deep Learning
    Wang, Yun
    Gao, Hongli
    Liu, Yuekai
    Guo, Liang
    Lu, Caijiang
    Li, Lei
    Liu, Yu
    Mao, Xianyin
    2019 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-QINGDAO), 2019,
  • [10] Deep Learning Based Power Transformer Monitoring Using Partial Discharge Patterns
    Prabhu, D. Karthik
    Maheswari, R., V
    Vigneshwaran, B.
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2022, 34 (03): : 1441 - 1454