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Classification of fault diagnosis in a gear wheel by used probabilistic neural network, fast Fourier transform and principal component analysis

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Author(s): Piotr CZECH

Journal: Transport Problems : an International Scientific Journal
ISSN 1896-0596

Volume: 2;
Issue: 4;
Start page: 99;
Date: 2007;
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Keywords: probabilistic neural network | fast Fourier transform | gear transmission

ABSTRACT
This paper presents the results of an experimental application of artificial neural network as a classifier of the degree of cracking of a tooth root in a gear wheel. The neural classifier was based on the artificial neural network of Probabilistic Neural Network type (PNN). The input data for the classifier was in a form of matrix composedof statistical measures, obtained from fast Fourier transform (FFT) and principal component analysis (PCA). The identified model of toothed gear transmission, operating in a circulating power system, served for generation of the teaching and testing set applied for the experiment.
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