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What is Short Circuit Fault Detection in PMSM about?
The paper presents a method for detecting short circuit faults (SCF) in permanent magnet synchronous motors (PMSM) using a Group Model of Data Handling deep neural network (GMDH-DNN). The proposed method achieves a detection accuracy of 99.2%, surpassing existing techniques such as CGAN, SVM, and KNN. This research highlights the effectiveness of deep learning in improving fault detection in electrical machines, particularly in reducing detection time and enhancing accuracy.
- Author
- debabnadjibadil
- Language
- EN