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...

Full description

Bibliographic Details
Main Authors: Bulgakov Grigoryevich Alexey, Nikolaevna-Kruglova Tatyana
Format: Article
Language:English
Published: Institut za istrazivanja i projektovanja u privredi 2017-01-01
Series:Istrazivanja i projektovanja za privredu
Subjects:
Online Access:https://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2017/1451-41171704426B.pdf
id doaj-b5a9d9e75d33424aa4ae5ebef51503c4
record_format Article
spelling 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
_version_ 1724165482692476928