Detecting Arcing Faults in Switchgear by Using Deep Learning Techniques

• Main Authors: Mohammed Alsumaidaee Y.A., Yaw C.T., Koh S.P., Tiong S.K., Chen C.P., Tan C.H., Ali K., Balasubramaniam Y.A.L.
• Other Authors: 58648412900
• Format: Article
• Published: MDPI 2024
• Subjects: 1D-CNN-LSTM; arcing; deep learning; energy; faults; switchgear

Switchgear and control gear are susceptible to arc problems that arise from slowly developing defects such as partial discharge, arcing, and heating due to faulty connections. These issues can now be detected and monitored using modern technology. This study aims to explore the effectiveness of deep...