ITM Web Conf.
Volume 28, 2019Computer Applications in Electrical Engineering (ZkwE’2019)
|Number of page(s)||2|
|Published online||15 July 2019|
Assessment of failure to the stator winding of the induction motor by means of deep neural network
Institute of Electrical Engineering and Electronics, Poznan University of Technology,
* Corresponding author: firstname.lastname@example.org
Due to the fact that inter-turn short-circuits are the ones of the most common causes of damage to stator of induction motors, research on their early detection is still gaining in importance. The scientific novelty in the presented article is an approach in which a decision element informing about the failure of stator of induction machine is a deep artificial neural network. In the learning process, torque waveforms subjected to a continuous wavelet transform were used. In order to classify of the stator winding failures the accelerator of artificial neural networks was used.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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