Applications of simplified fuzzy ARTMAP to partial discharge classification and pattern recognition

Artificial intelligent techniques have been widely used in high voltage insulation technology application. In this paper, the effectiveness of artificial intelligent technique to apply for pattern recognition and classification of Partial Discharge (PD) is presented. Partial discharge signal was generated and measured by using an artificial partial discharge source. Characteristics of PD signal for pattern recognition and classification were determined by using statistical and fractal methods from relationship among the voltage phase angle, the discharge magnitude and the repeated existing of partial discharges. The simplified fuzzy ARTMAP (SFAM) was used as artificial intelligent technique for pattern recognition and classification. PDs characteristic quantities were used as input parameters for Simplified Fuzzy ARTMAP to train pattern recognition and classification system. Pattern recognition and classification results were obtained. The results demonstrated the high effectiveness of the purpose technique applied for pattern recognition and classification of partial discharge.

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