Intelligent method of electric drive diagnostic with due account for its operation mode
In this article is proposed an intelligent method for diagnosing a technical condition, which makes it possible to distinguish a true malfunction of object from changing the parameters of its operating mode. As a result of numerous experiments has been revealed the dependence of measurement of wavel...
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Institut za istrazivanja i projektovanja u privredi
2017-01-01
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Online Access: | https://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2017/1451-41171704426B.pdf |
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doaj-b5a9d9e75d33424aa4ae5ebef51503c42021-04-02T11:11:49ZengInstitut za istrazivanja i projektovanja u privrediIstrazivanja i projektovanja za privredu1451-41171821-31972017-01-011544264321451-41171704426BIntelligent method of electric drive diagnostic with due account for its operation modeBulgakov Grigoryevich Alexey0Nikolaevna-Kruglova Tatyana1Southwest State University, Kursk, RussiaSouth-Russian State Polytechnic University, Novocherkassk, RusiaIn this article is proposed an intelligent method for diagnosing a technical condition, which makes it possible to distinguish a true malfunction of object from changing the parameters of its operating mode. As a result of numerous experiments has been revealed the dependence of measurement of wavelet transformation coefficients on the characteristic scales of a serviceable and faulty engine under different loading regimes. On the basis of the received information has been developed a neural classification network which makes it possible to reveal the current state of the object. Further studies have shown that any parent wavelet can be used to implement the proposed method. The study of the state of the drive under various loads confirms the correctness of the theoretical calculations and the adequacy of the model.https://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2017/1451-41171704426B.pdfdiagnosis of the electric driveneural network methodwavelet transformationoperating mode of the drive |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bulgakov Grigoryevich Alexey Nikolaevna-Kruglova Tatyana |
spellingShingle |
Bulgakov Grigoryevich Alexey Nikolaevna-Kruglova Tatyana Intelligent method of electric drive diagnostic with due account for its operation mode Istrazivanja i projektovanja za privredu diagnosis of the electric drive neural network method wavelet transformation operating mode of the drive |
author_facet |
Bulgakov Grigoryevich Alexey Nikolaevna-Kruglova Tatyana |
author_sort |
Bulgakov Grigoryevich Alexey |
title |
Intelligent method of electric drive diagnostic with due account for its operation mode |
title_short |
Intelligent method of electric drive diagnostic with due account for its operation mode |
title_full |
Intelligent method of electric drive diagnostic with due account for its operation mode |
title_fullStr |
Intelligent method of electric drive diagnostic with due account for its operation mode |
title_full_unstemmed |
Intelligent method of electric drive diagnostic with due account for its operation mode |
title_sort |
intelligent method of electric drive diagnostic with due account for its operation mode |
publisher |
Institut za istrazivanja i projektovanja u privredi |
series |
Istrazivanja i projektovanja za privredu |
issn |
1451-4117 1821-3197 |
publishDate |
2017-01-01 |
description |
In this article is proposed an intelligent method for diagnosing a technical condition, which makes it possible to distinguish a true malfunction of object from changing the parameters of its operating mode. As a result of numerous experiments has been revealed the dependence of measurement of wavelet transformation coefficients on the characteristic scales of a serviceable and faulty engine under different loading regimes. On the basis of the received information has been developed a neural classification network which makes it possible to reveal the current state of the object. Further studies have shown that any parent wavelet can be used to implement the proposed method. The study of the state of the drive under various loads confirms the correctness of the theoretical calculations and the adequacy of the model. |
topic |
diagnosis of the electric drive neural network method wavelet transformation operating mode of the drive |
url |
https://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2017/1451-41171704426B.pdf |
work_keys_str_mv |
AT bulgakovgrigoryevichalexey intelligentmethodofelectricdrivediagnosticwithdueaccountforitsoperationmode AT nikolaevnakruglovatatyana intelligentmethodofelectricdrivediagnosticwithdueaccountforitsoperationmode |
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1724165482692476928 |