Publications:Unsupervised deviation detection by GMM - A simulation study

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Title Unsupervised deviation detection by GMM - A simulation study
Author Magnus Svensson and Thorsteinn Rögnvaldsson and Stefan Byttner and Martin West and Björn Andersson
Year 2011
PublicationType Conference Paper
Journal
HostPublication SDEMPED 2011 : 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics & Drives : September 5-8, 2011, Bologna, Italy
Conference 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2011, Bologna, Italy, 5-8 September, 2011
DOI http://dx.doi.org/10.1109/DEMPED.2011.6063601
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:439142
Abstract A new approach to improve fault detection of electrical machines is proposed. The increased usage of electrical machines and the higher demands on their availability requires new approaches to fault detection. In this paper we demonstrate that it is possible to detect a certain fault on a PMSM (Permanent Magnet Synchronous Machine) by using multiple similar motors, or a single motor, to build a norm of expected behavior by monitoring signal relations. This means that the machine is monitored in an unsupervised way. Four levels of an increased temperature in the rotor magnets have been investigated. The results are based on simulations and the signals used (for relation measurements) are available in a real motor installation. The method shows promising results in detecting two of the temperature faults. © 2011 IEEE.