By Topic

Impulse testing for detection of insulation failure of motor winding and diagnosis based on Hidden Markov Model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Hisahide Nakamura ; R&D Division, TOENEC Corporation 1-79, Takiharu-cho, Minami-ku Nagoya, 457-0819, Japan ; Masaaki Chihara ; Tomokazu Inoki ; Taizo Higaki
more authors

Short circuit fault of a motor, due to breakdown of an insulating material of winding, is one of the most probable faults in motor drive systems. Establishment of an easy and effective fault diagnosis method has been strongly required to assure operation with high reliability. This paper proposes a novel diagnosis method for insulation failure of motor windings by a combination of impulse testing and pattern recognition based on Hidden Markov Model (HMM). A voltage waveform across two winding terminals is recorded under application of an impulse voltage. HMM is exploited to distinguish a small difference in voltage waveforms between healthy and faulty winding insulations. Usefulness of the proposed diagnostic method is verified through voltage waveforms experimentally obtained for motors with several kinds of turn-to-turn insulation failures.

Published in:

IEEE Transactions on Dielectrics and Electrical Insulation  (Volume:17 ,  Issue: 5 )