NDLI: Use of data standardization to improve inverter - induction machine fault detection

Content Provider	IEEE Xplore Digital Library
Author	Ondel, O. Boutleux, E. Clerc, G.
Copyright Year	2006
Description	Author affiliation: Centre de Genie Electrique de Luon, Ecole Centrale de Lyon, Ecully (Ondel, O.; Boutleux, E.)
Abstract	Intensive research efforts have been focused on the signature analysis (SA) to detect electrical and mechanical fault condition of induction machines. Different signals can be used: voltage, current and flux. The characteristic frequency research by a current spectral analysis is a well-known method widely used. This method is valid when the motor is supplied by the three-phase main network. However nowadays, in industrials applications, the asynchronous motors are more and more supplied by converters, in particular for variable speed. The current spectral analysis is almost not exploitable because of appearance of multiple harmonics of the commutation frequency. This paper presents a diagnosis method applied to a set "converter-machine-load". This method is based on pattern recognition approach. The use of the data standardization makes it possible to free from the level of load and thus to represent an operating mode by only one class. This fact allows decreasing the number of initial data necessary to the training phase and improving the final diagnosis
Starting Page	5034
Ending Page	5039
File Size	7357860
Page Count	6
File Format	PDF
ISBN	1424403901
ISSN	1553572X
DOI	10.1109/IECON.2006.347463
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-06
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Standardization Inverters Induction machines Fault detection Electrical fault detection Frequency Spectral analysis Voltage Commutation Pattern recognition converter-machine-load Diagnosis pattern recognition data standardization
Content Type	Text
Resource Type	Article

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