Inter Turn Short-Circuit Detection In Vector Controlled Pms Motor Using Ai

Abstract

This paper deals with the diagnostics of inter turn faults in a vector controlled synchronous motor with permanent magnets. Inter turn faults are detected by a convolution neural network from adequately preprocessed current signals of the stator phases. The goal is to create a model within which different severity of inter turn faults will be simulated. Data from the simulations are preprocessed and transformed using Wavelet transform and the resulting scalograms are fed to a pre-trained convolution neural network GoogLeNet. This neural network’s diagnostic capabilities are tested on a physical drive, capable of emulating faults.