Design of partial discharge location identifier software for high voltage generator using artificial neural network

This paper deals with design of software for partial discharge (PD) pattern recognition and signal assessment on power generator using artificial neural network (ANN). The identified PD signal was the simulation of PD measurement result on high voltage generator. The simulated signal contains background noise (BGN) and phase-resolved PD pattern (PRPD pattern) data. The characteristics of information processing systems of ANN is similar to biological neural networks. ANN method is a decision making system using the learning system that works based on knowledge based database. PD pattern recognition is done by observing the phase of PD signal, while the PD location identification of the high voltage generator is adapted based on the standards and also previous studies on the phase of PRPD pattern. Database is obtained from PD data collection results of PRPD signal simulation. The performance of the software is tested in determining the PD location on the generator. The software testing is done by providing a data test of PRPD patterns and BGN. This testing results showed that the software has been proven to have a high accuracy degree for PD pattern recognition.