Neuronové sítě a diagnostika izolačních materiálů pro vinutí elektrických strojů

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

článek ve sborníku ve WoS nebo Scopus

cs

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 architecture 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 simulations and the values calculated were also obtained by means of this product.

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 architecture 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 simulations and the values calculated were also obtained by means of this product.

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 architecture 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 simulations and the values calculated were also obtained by means of this product.

Diagnostic, Artifical inteligence, Neural networks, Modelling, Identification, Simulation

01.01.2002

Academia centrum Univerzity Tomáše Bati ve Zlíně

Zlín, Česká republika

80-7318-076-6

TD 2002 - DIAGON 2002

6