PD monitor system for power generators

This paper introduces a computerized PD monitoring system for generators and presents the experimental and numerical study of discharge pattern recognition methods. The system has specially designed transducers, data acquisition unit and software, and can obtain statistical as well as individual discharge information. In order to validate the performance of the system, experiments were done in the laboratory, using elaborately designed models that can generate various types of discharges. Feature extraction of the gathered data and neural network (NN) classification of the acquired discharge patterns were studied. The results showed that the surface fitting method is able to extract features from statistical data of discharges, and that NN is a potential classifier in practical applications.