Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Dielectrics and Electrical Insulation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
