The neural networks and diagnostic of insulating materials for electrical machine windings

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F02%3APU30611" target="_blank" >RIV/00216305:26210/02:PU30611 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

čeština

Original language name

Neuronové sítě a diagnostika izolačních materiálů pro vinutí elektrických strojů

Original language description

The contribution deals with the use of artifical inteligence methods in the life diagnostics of Relanex insulating material that is applied as insulation of electrical machine windings. For example, neural networks are one applicable method. The method belongs to the appropriate tools that provide the modelling, identification and simulation of technological systems and units. In such a case, the insulating material is used as a modelled and identified system. The first part of the paper describes the aarchitecture and the setting of neural networks, the description of input modelled and identified data. The second part shows (in the figures) the curves of identification, modelling and the simulation of insulating material behaviour with neural networks. Tables evaluate the application of this tool for the solution of the problems investigated. We have used the above-mentioned neural networks for the diagnostics of insulating materials that were programmed in Matlab 6 environment. All

Czech name

Neuronové sítě a diagnostika izolačních materiálů pro vinutí elektrických strojů

Czech description

The contribution deals with the use of artifical inteligence methods in the life diagnostics of Relanex insulating material that is applied as insulation of electrical machine windings. For example, neural networks are one applicable method. The method belongs to the appropriate tools that provide the modelling, identification and simulation of technological systems and units. In such a case, the insulating material is used as a modelled and identified system. The first part of the paper describes the aarchitecture and the setting of neural networks, the description of input modelled and identified data. The second part shows (in the figures) the curves of identification, modelling and the simulation of insulating material behaviour with neural networks. Tables evaluate the application of this tool for the solution of the problems investigated. We have used the above-mentioned neural networks for the diagnostics of insulating materials that were programmed in Matlab 6 environment. All

Type

D - Article in proceedings

CEP classification

JA - Electronics and optoelectronics

OECD FORD branch

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Project

<a href="/en/project/GA102%2F03%2F0621" target="_blank" >GA102/03/0621: Irreversible processes in insulating materials for high temperature</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2002

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

TD 2002 - DIAGON 2002

ISBN

80-7318-076-6

ISSN

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e-ISSN

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Number of pages

6

Pages from-to

63-68

Publisher name

Academia centrum Univerzity Tomáše Bati ve Zlíně

Place of publication

Zlín, Česká republika

Event location

Zlín

Event date

May 21, 2002

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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