Application of genetic algorithms in the task of choosing inputs for probabilistic neural network classifier of faults of gear-tooth

• Autorzy: Czech P. , Mikulski J.
• Języki publikacji: EN

Abstrakty

EN

In this article are presented results of trials of building an application based on probabilistic neural network, used to diagnose damages to the gear wheel teeth in the form of cracks at the base of the tooth. To determine the proper network learning process is necessary to get from the tested object numerous set of input data. Conducted researches are based on data obtained from the identified model of gear working in the drive system, which made it possible to acquire the necessary amount of data. In experiments was tested the usefulness of different sets of descriptors of teeth damages, constructed on the basis of vibratory signals, processed using the Wigner-Ville transform. Often the problem, which makes the proper learning of the neural classifiers impossible is the size of the network structure. Therefore, in further studies was examined the usefulness of genetic algorithms which task is selecting an input data for the artificial neural networks of PNN type.

Słowa kluczowe

EN

gearbox; diagnostics; neural networks; Wigner-Ville transform; genetic algorithm

PL

skrzynia biegów; diagnostyka; sieci neuronowe; transformata Wignera-Ville'a; algorytm genetyczny

• Wydawca: Polskie Stowarzyszenie Telematyki Transportu
• Czasopismo: Archives of Transport System Telematics
• Rocznik: 2015
• Tom: Vol. 8, iss. 3
• Strony: 15--19
• Opis fizyczny: Bibliogr. 20 poz.

Twórcy

autor

Czech P.

• Silesian University of Technology, Faculty of Transport, Krasinskiego 8, 40-019 Katowice, Poland

autor

Mikulski J.

• University of Economics in Katowice, Faculty of Economics, 1 Maja 47, 40-228 Katowice, Poland

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