Fault Diagnosis of Power Cable Based on 1DCNN-BiLSTM

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Fault Diagnosis of Power Cable Based on 1DCNN-BiLSTM

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[1]GAO Chao,LIU Zehui,CAO Dong,et al.Fault Diagnosis of Power Cable Based on 1DCNN-BiLSTM[J].Journal of Zhengzhou University (Engineering Science),2023,44(05):86-92.[doi:10.13705/j.issn.1671-6833.2023.02.011]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 44 Number of periods: 2023 05 Page number: 86-92 Column: Public date: 2023-08-20

Title:: Fault Diagnosis of Power Cable Based on 1DCNN-BiLSTM

Author(s):: GAO Chao¹ ; LIU Zehui¹; CAO Dong²; YAO Lina²; 1. State Grid Henan Electric Power Company Economic and Technological Research Institute, Zhengzhou 450052, China; 2. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China

Keywords:: power cable; fault diagnosis; one-dimensional convolutional neural network; bidirectional long shortterm memory network; short circuit

CLC:: TM732

DOI:: 10.13705/j.issn.1671-6833.2023.02.011

Abstract:: In order to improve the accuracy of fault diagnosis of power cable failure to ensure a cable fault detection method based on convolution neural network (CNN) and bi-directional long short term memory (BiLSTM) was proposed in this paper. The simulation model was built through Simulink to extract the voltage signals of single-phase ground short circuit, two-phase ground short circuit, two-phase phase short circuit and three-phase short circuit faults, and to generate the fault sample. Then the fault voltage signals were input into the network model, to obtain the local features through CNN, to obtain the fault signal timing information through BiLSTM, and to realize the diagnosis of cable fault based on the automatically extracted features. The simulation results showed that this method could accurately classify the four short-circuit faults of power cables, the accuracy rate of single-phase grounding short-circuit fault and three-phase short-circuit fault was 97%, the accuracy rate of two-phase ground short circuit and two-phase short circuit was 92%, and the overall accuracy rate was 98. 37%. In addition, through the analysis of loss function curve and accuracy curve, it was proved that this method could achieve better cable fault diagnosis effectiveness. Finally, the actual data was used to verify the feasibility of the method.

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Last Update: 2023-09-04