A New Adaptive Intelligent DC motors Fault Diagnosis System Using R-WDCNN Classifier

Conventional diagnostic approaches for DC motors often require extensive expertise and are labor-intensive. These traditional methods also tend to be less efficient and accurate. In light of these issues, we have introduced a novel, smart diagnostic process for DC motors utilizing wide-kernel residu...

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Veröffentlicht in:	2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET) S. 1217 - 1220
Hauptverfasser:	Xie, Yonghui, Qin, Huabin, Yin, Haihong, Hou, Xujie
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 17.05.2024
Schlagworte:	Accuracy adaptive batch normalization algorithm Classification algorithms Convolutional neural networks DC motors Fault diagnosis Feature extraction Manuals Residual deep convolutional neural networks residual learning wide first-layer kernels
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