Detail publikace

LIFETIME PREDICTION OF INSULATING MATERIALS BY FUZZY-NEURAL NETWORKS AND EXPERT SYSTEMS

Originální název

LIFETIME PREDICTION OF INSULATING MATERIALS BY FUZZY-NEURAL NETWORKS AND EXPERT SYSTEMS

Anglický název

LIFETIME PREDICTION OF INSULATING MATERIALS BY FUZZY-NEURAL NETWORKS AND EXPERT SYSTEMS

Jazyk

en

Originální abstrakt

The paper deals with searching for new methods of diagnostics and lifetime prediction of insulating materials of electric rotary machines windings. The subject of the diagnostics is to specify the condition of insulation used. In this time, the most popular diagnostics tools are the methods of artificial intelligence like expert systems and fuzzy neural networks. In our research we are using expert system for diagnostics of insulating material and fuzzy neural network for lifetime prediction of this material. Input of those systems is Bv (activation energy) which was obtained by non-destructive measurement method. The determination of this quantity is the main prerequisite for the determination of output coefficient Up (breakdown voltage) characterizing the lifetime of the insulating system and, consequently, the whole electric machine.

Anglický abstrakt

The paper deals with searching for new methods of diagnostics and lifetime prediction of insulating materials of electric rotary machines windings. The subject of the diagnostics is to specify the condition of insulation used. In this time, the most popular diagnostics tools are the methods of artificial intelligence like expert systems and fuzzy neural networks. In our research we are using expert system for diagnostics of insulating material and fuzzy neural network for lifetime prediction of this material. Input of those systems is Bv (activation energy) which was obtained by non-destructive measurement method. The determination of this quantity is the main prerequisite for the determination of output coefficient Up (breakdown voltage) characterizing the lifetime of the insulating system and, consequently, the whole electric machine.

BibTex


@inproceedings{BUT17945,
  author="Miloš {Hammer} and Zbyněk {Říha} and Petr {Latina}",
  title="LIFETIME PREDICTION OF INSULATING MATERIALS BY FUZZY-NEURAL NETWORKS AND EXPERT SYSTEMS",
  annote="The paper deals with searching for new methods of diagnostics and lifetime prediction of insulating materials of electric rotary machines windings. The subject of the diagnostics is to specify the condition of insulation used. In this time, the most popular diagnostics tools are the methods of artificial intelligence like expert systems and fuzzy neural networks. In our research we are using expert system for diagnostics of insulating material and fuzzy neural network for lifetime prediction of this material. Input of those systems is Bv (activation energy) which was obtained by non-destructive measurement method. The determination of this quantity is the main prerequisite for the determination of output coefficient Up (breakdown voltage) characterizing the lifetime of the insulating system and, consequently, the whole electric machine.",
  address="University of Salerno",
  booktitle="ICPR-18",
  chapter="17945",
  howpublished="print",
  institution="University of Salerno",
  year="2005",
  month="september",
  pages="----",
  publisher="University of Salerno",
  type="conference paper"
}