Geodesic
Method of identification of electrical motor with the use of neural networks
Problemy fiziki, matematiki i tehniki, no. 3 (2013), pp. 97-99.

Voir la notice de l'article provenant de la source Math-Net.Ru

Different kinds of malfunction or damage of the parts may occur in the operation of electrical equipment. It is therefore very important to detect defects in the early stages. The paper presents the method of identification of electrical equipment on the basis of the analysis of the products current. The results of experimental tests are given.
Mots-clés : identification, spectral noise
Keywords: high harmonic, neural network. 
@article{PFMT_2013_3_a16,
     author = {D. I. Kuznetsov and A. I. Kupin},
     title = {Method of identification of electrical motor with the use of neural networks},
     journal = {Problemy fiziki, matematiki i tehniki},
     pages = {97--99},
     publisher = {mathdoc},
     number = {3},
     year = {2013},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/PFMT_2013_3_a16/}
}
TY  - JOUR
AU  - D. I. Kuznetsov
AU  - A. I. Kupin
TI  - Method of identification of electrical motor with the use of neural networks
JO  - Problemy fiziki, matematiki i tehniki
PY  - 2013
SP  - 97
EP  - 99
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/PFMT_2013_3_a16/
LA  - ru
ID  - PFMT_2013_3_a16
ER  - 
%0 Journal Article
%A D. I. Kuznetsov
%A A. I. Kupin
%T Method of identification of electrical motor with the use of neural networks
%J Problemy fiziki, matematiki i tehniki
%D 2013
%P 97-99
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/PFMT_2013_3_a16/
%G ru
%F PFMT_2013_3_a16
D. I. Kuznetsov; A. I. Kupin. Method of identification of electrical motor with the use of neural networks. Problemy fiziki, matematiki i tehniki, no. 3 (2013), pp. 97-99. http://geodesic.mathdoc.fr/item/PFMT_2013_3_a16/

[1] V. M. Kravchenko, V. A. Sidorov, Tekhnicheskoe diagnostirovanie mekhanicheskogo oborudovaniya, Donetsk, 2006, 330 pp.

[2] D. A. Ostapenko, “Problema kachestvennogo elektrosnabzheniya”, Novosti elektrotekhniki, 2007, no. 4 (46), 17–18

[3] V. S. Petukhov, V. A. Sokolov, “Diagnostika sostoyaniya elektrodvigatelei na osnove spektralnogo analiza potreblyaemogo toka”, Novosti elektrotekhniki, 2005, no. 1 (31), 23–24

[4] G. Didier et al., “Fault detection of broken rotor bars in induction motor using a global fault Index”, IEEE Transactions on Industry Applications, 42 (2006), 79–88 | DOI