Abstract
Partial discharge (PD) detection plays a fundamental role in monitoring the health of medium voltage (MV) systems. This paper presents a method for PD detection and source recognition in MV sub-stations based on a combination of signal processing techniques. Firstly, PD detection and signal conditioning is carried out. Then, PDs of different sources are separated and finally classified by means of the extension set theory. The obtained results show a classification effectiveness of 100% on single source PDs and an effectiveness of 72.5% in multisource PDs, where PDs from many sources are captured in the same data set.
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 callDisclaimer: 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.
