A novel approach to corona monitoring

  • Authors:

  • Chiman Kwan;Tao Qian;Zhubing Ren;Hongda Chen;Roger Xu;Weijen Lee;Hemiao Zhang;Joseph Sheeley

  • Affiliations:

  • Intelligent Automation, Inc., Rockville, MD;Intelligent Automation, Inc., Rockville, MD;Intelligent Automation, Inc., Rockville, MD;Intelligent Automation, Inc., Rockville, MD;Intelligent Automation, Inc., Rockville, MD;Electrical Engineering Dept, University of Texas at Arlington, Arlington, TX;Electrical Engineering Dept, University of Texas at Arlington, Arlington, TX;Arnold Air Force Base, Tennessee, TN

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2005

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Abstract

Corona discharge (CD) and partial discharge (PD) indicate early stages of insulation problems in motors. Early detection of CD/PD will enable better coordination and planning of resources such as maintenance personnel, ordering of parts, etc. Most importantly, one can prevent catastrophic failures during normal operations. In this paper, we summarize the application of Support Vector Machine (SVM) to CD/PD monitoring. Hardware testbeds have been developed to emulate CD/PD behaviors and real-time experimental results showed the effectiveness of SVM for fault detection and classification.