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Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT and Bayes classifier

Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT... Abstract In this article results of diagnostic investigations of separately excited DC motor were presented. In diagnostics were applied a Fourier analysis method based on the fast Fourier transform (FFT) and a recognition method using Bayes classifier. In training process a set of the most important frequencies has been determined for which differences of corresponding signals in two states are the largest. Three categories of signals have been recognized in identification process: faultless state, state of the rotor broken one coil and state of the rotor shorted three coils. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Electrical Engineering de Gruyter

Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT and Bayes classifier

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
2300-2506
eISSN
2300-2506
DOI
10.1515/aee-2015-0004
Publisher site
See Article on Publisher Site

Abstract

Abstract In this article results of diagnostic investigations of separately excited DC motor were presented. In diagnostics were applied a Fourier analysis method based on the fast Fourier transform (FFT) and a recognition method using Bayes classifier. In training process a set of the most important frequencies has been determined for which differences of corresponding signals in two states are the largest. Three categories of signals have been recognized in identification process: faultless state, state of the rotor broken one coil and state of the rotor shorted three coils.

Journal

Archives of Electrical Engineeringde Gruyter

Published: Mar 1, 2015

References