Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2009

Abstract

Unlike a fixed-frequency power supply, the voltagesupplying an inverter-fed motor is heavily corrupted by noises,which are produced from high-frequency switching leading tonoisy stator currents. To extract useful information from statorcurrentmeasurements, a theoretically sound and robust denoisingmethod is required. The effective filtering of these noisesis difficult with certain frequency-domain techniques, such asFourier transform or Wavelet analysis, because some noises havefrequencies overlapping with those of the actual signals, andsome have high noise-to-frequency ratios. In order to analyze thestatistical signatures of different types of signals, a certainnumber is required of the individual signals to be de-noisedwithout sacrificing the individual characteristic and quantity ofthe signals. An ensemble and individual noised reduction (EINR)method is proposed as the extension of the common averagingmethod for induction-motor signature analysis. The signals afterde-noising by the proposed EINR method will preserve theindividual characteristics. A number of signals are selected as anensemble part in the proposed EINR method and are employedas the “profile” to de-noise other individual signals. The casestudy presented in this paper demonstrates the merits of theproposed EINR method for induction-motor signature analysis.

Keywords

Noise, Ensemble and individual noise reduction, Induction motor, Signature analysis, Stator current.

Discipline

Databases and Information Systems | Information Security

Research Areas

Data Science and Engineering

Publication

Proceedings of the 8th IET International Conference on Advances in Power System Control, Operation and Management, Hong Kong, China, 2009 November 8-11.

ISBN

9781849192149

Identifier

10.1049/cp.2009.1845

Publisher

Institute of Engineering and Technology

City or Country

England

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