SA-ConSinGAN and reservoir computing fusion for accurate bearing fault classification and severity identification using GAF-based techniques
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Researchers are exploring new methods for fault classification and severity identification in bearings and transformers. A fusion of SA-ConSinGAN and reservoir computing is being used for bearing fault diagnosis, while another approach utilizes Gramian Angular Field and optimized parallel ShuffleNetV2 for transformer fault diagnosis. The techniques being developed involve various algorithms and models, including GAF-based techniques.