Detail publikace

THE LIFETIME PREDICTION OF INSULATING MATERIAL BY FUZZY NEURAL NETWORKS

Originální název

THE LIFETIME PREDICTION OF INSULATING MATERIAL BY FUZZY NEURAL NETWORKS

Anglický název

THE LIFETIME PREDICTION OF INSULATING MATERIAL BY FUZZY NEURAL NETWORKS

Jazyk

en

Originální abstrakt

The paper deals with the diagnostics of insulating materials of electric rotating machines using fuzzy neural networks, the effect of the input values and the setting of the fuzzy neural network on the result of prediction and simulation of insulating material. The input data consist of coefficients Ba (activation energy of a polarization action), Bv (activation energy of a conduction action) and Uk, being a parameter that determines critical voltage. The data is acquired by non-destructive measurement on insulating material samples. They are the main prerequisites for the prediction of coefficient Up (break-down voltage) that characterizes the lifetime of the insulating material and, therefore, the whole motor. The fuzzy neural networks were programmed in the Matlab 6.5 environment and the results of simulations were obtained using the same product.

Anglický abstrakt

The paper deals with the diagnostics of insulating materials of electric rotating machines using fuzzy neural networks, the effect of the input values and the setting of the fuzzy neural network on the result of prediction and simulation of insulating material. The input data consist of coefficients Ba (activation energy of a polarization action), Bv (activation energy of a conduction action) and Uk, being a parameter that determines critical voltage. The data is acquired by non-destructive measurement on insulating material samples. They are the main prerequisites for the prediction of coefficient Up (break-down voltage) that characterizes the lifetime of the insulating material and, therefore, the whole motor. The fuzzy neural networks were programmed in the Matlab 6.5 environment and the results of simulations were obtained using the same product.

BibTex


@inproceedings{BUT18409,
  author="Miloš {Hammer} and Zbyněk {Říha} and Petr {Latina}",
  title="THE LIFETIME PREDICTION OF INSULATING MATERIAL BY FUZZY NEURAL NETWORKS",
  annote="The paper deals with the diagnostics of insulating materials of electric rotating machines using fuzzy neural networks, the effect of the input values and the setting of the fuzzy neural network on the result of prediction and simulation of insulating material. The input data consist of coefficients Ba (activation energy of a polarization action), Bv (activation energy of a conduction action) and Uk, being a parameter that determines critical voltage. The data is acquired by non-destructive measurement on insulating material samples. They are the main prerequisites for the prediction of coefficient Up (break-down voltage) that characterizes the lifetime of the insulating material and, therefore, the whole motor. The fuzzy neural networks were programmed in the Matlab 6.5 environment and the results of simulations were obtained using the same product.",
  address="Oficyna Wydawnicza Politechniki Opolskiej - opole 2005",
  booktitle="SME 2005",
  chapter="18409",
  howpublished="print",
  institution="Oficyna Wydawnicza Politechniki Opolskiej - opole 2005",
  year="2005",
  month="june",
  pages="509--512",
  publisher="Oficyna Wydawnicza Politechniki Opolskiej - opole 2005",
  type="conference paper"
}