Fault Detection for Medium Voltage Switchgear Using a Deep Learning Hybrid 1D-CNN-LSTM Model

• 主要な著者: Alsumaidaee Y.A.M., Paw J.K.S., Yaw C.T., Tiong S.K., Chen C.P., Yusaf T., Benedict F., Kadirgama K., Hong T.C., Abdalla A.N.
• その他の著者: 58648412900
• フォーマット: 論文
• 出版事項: Institute of Electrical and Electronics Engineers Inc. 2024
• 主題: arcing fault; deep learning; Energy; fault detection; hybrid model; medium voltage switchgear; power system safety; Accident prevention; Deep learning; Electric power system control; Fault detection; Finite difference method; Frequency domain analysis; Arcing faults; Corona; Faults detection; Faults diagnosis; Hybrid model; Medium voltage; Medium voltage switchgears; Power system safeties; Ultrasonic imaging

Medium voltage (MV) switchgear is a vital part of modern power systems, responsible for regulating the flow of electrical power and ensuring the safety of equipment and personnel. However, switchgear can experience various types of faults that can compromise its reliability and safety. Common faults...