Publication detail

THE USE OF NEURAL NETWORK FOR DIAGNOSTICS REMANENT LIFETIME OF INSULATING MATERIAL

HAMMER, M. LATINA, P. ŘÍHA, Z.

Czech title

POUŽITÍ NEURONOVÁ SÍTĚ PRO DIAGNOSTIKU ZBYTKOVÉ DOBY ŽIVOTNOSTI IZOLANTU

English title

THE USE OF NEURAL NETWORK FOR DIAGNOSTICS REMANENT LIFETIME OF INSULATING MATERIAL

Type

conference paper

Language

en

Original abstract

The paper deals with the usage of artificial intelligence (neural networks) for description the lifetime of insulating material of electric rotary machine. A state of insulating material is the main part of reliability of whole system. Up to now, we worked with data obtained by non-destructive method in laboratory condition on insulating sample. At this time, we are trying to apply the data, which were measured by non-destructive method too. The data were measured on real electric motor and they will be used for inputs of the neural network. The neural network then can predict the remanent lifetime of investigate system

Czech abstract

Příspěvek se zabývá využitím umělé inteligence pro popis životnosti izolačního materiálu elektrického točivého stroje. Stav konkrétního izolačního materiálu je jistě důležitou částí správné funkce celého sledovaného objektu, tj. elektrického točivého stroje. Náš ústav se již několik let zabývá použitím neuronových sítí k popisu kondice izolačního materiálu. Doposud jsme stav izolačního materiálu řešili s daty získanými měřením na vzorku izolačního materiálu nedestruktivní metodou. Nyní se náš výzkum zabývá problémem, zda budou neuronové sítě vhodným a efektivním nástrojem pro diagnostiku i s daty naměřenými na reálném stroji.

English abstract

The paper deals with the usage of artificial intelligence (neural networks) for description the lifetime of insulating material of electric rotary machine. A state of insulating material is the main part of reliability of whole system. Up to now, we worked with data obtained by non-destructive method in laboratory condition on insulating sample. At this time, we are trying to apply the data, which were measured by non-destructive method too. The data were measured on real electric motor and they will be used for inputs of the neural network. The neural network then can predict the remanent lifetime of investigate system

Keywords in Czech

Neuronová síť; Diagnostika; Umělá Intelligence

Keywords in English

Neural Network; Diagnostic; Artificial Intelligence

RIV year

2005

Released

09.06.2005

Location

Sibiu, Romania

ISBN

973-718-259-6

Book

UBR-CORR Study and Control of Corroslon in the Perspective of Sustalnable Development of Urban Distribution Grids

Pages from–to

163–165

Pages count

3

BIBTEX


@inproceedings{BUT18414,
  author="Miloš {Hammer} and Petr {Latina} and Zbyněk {Říha},
  title="THE USE OF NEURAL NETWORK FOR DIAGNOSTICS REMANENT LIFETIME OF INSULATING MATERIAL",
  booktitle="UBR-CORR Study and Control of Corroslon in the Perspective of Sustalnable Development of Urban Distribution Grids",
  year="2005",
  month="June",
  pages="163--165",
  address="Sibiu, Romania",
  isbn="973-718-259-6"
}