所蔵: Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment. The root cause of this issue is an electrical breakdown...

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主要な著者:	Mohammed Alsumaidaee Y.A., Yaw C.T., Koh S.P., Tiong S.K., Chen C.P., Yusaf T., Abdalla A.N., Ali K., Raj A.A.
その他の著者:	58648412900
フォーマット:	論文
出版事項:	MDPI 2024
主題:	1D-CNN-LSTM corona discharge energy faults switchgear Air quality Electric corona Fault detection Flashover Learning systems Long short-term memory Time domain analysis 1d-CNN-LSTM Corona discharges Damaging effects Electrical equipment Electrical stress Energy Fault Medium voltage Metal-clad Time and frequency domains algorithm article deep learning human learning long short term memory network physiological stress sound worker Frequency domain analysis
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Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods

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