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

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Date
2020
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Mark
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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.
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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
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Peer-reviewed
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cs
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© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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