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

Zezula, Lukáš

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

Files

63-eeict_1.pdf(826.46 KB)

Date

2020

Authors

Zezula, Lukáš

Publisher

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

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.

Keywords

PMSM, ITF, Inter turn fault, Inter turn short-circuit, Vector control, Convolutional neural network, Motor fault diagnostics

Citation

Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 63-66. ISBN 978-80-214-5867-3
https://conf.feec.vutbr.cz/eeict/EEICT2020

Document type

Peer-reviewed

Document version

Published version

Language of document

cs

Document licence