On Model-Based Transfer Learning Method for the Detection of Inter-Turn Short Circuit Faults in PMSM.

The early detection of an inter-turn short circuit (ITSC) fault is extremely critical for permanent magnet synchronous motors (PMSMs) because it can lead to catastrophic consequences. In this study, a model-based transfer learning method is developed for ITSC fault detection. The contribution can be summarized as two points.

Multiscale Kernel-Based Residual CNN for Estimation of Inter-Turn Short Circuit Fault in PMSM.

The diagnosis of an inter-turn short circuit (ITSC) fault at its early stage is very important in permanent magnet synchronous motors as these faults can lead to disastrous results. In this paper, a multiscale kernel-based residual convolutional neural network (CNN) algorithm is proposed for the diagnosis of ITSC faults. The contributions are majorly located on two sides.