The Life Prediction of Insulating Materials for Electric Machines with Insulating Materials

conference paper

English

The life of the insulating systems of electric rotary machines is strongly depent upon electrical and thermal features of the insulating material used. The subject of the diagnistic prediction is to specify the condition of insulation used. At present days, the most popular prediction tools are the methods of artifical intelligence, and one method is the neural networks. This paper is concentrated on the use of neural networks in the life prediction of Relanex insulating material that is applied as insulation of electric machine windings. In this case, the condition of insulating in a time step k+1 is predicated from input quantity in time steps k, k-1, k-2, etc. Anyway the prediction means forecasting of quantity in future form N previous measurement this or other quantities in the past. The first part of the paper describes the use of artificial neural networks which forecast the life of insulating material for windings in electric rotary machines, the description of training and test data and setting of neural network for prediction. The second part shows (in the figures) the curves of prediction 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 prediction of insulating materials that were programmed in the Matlab 6 enviroment. All simulations and the values calculated were also obtained by means of this product.

Insulating Materials

HAMMER, M.

1. 1. 2003

University of South Florida

Tampa - Florida

426

437

12