Ensemble and individual noise reduction method for induction-motor signature analysis

• Main Authors: WANG, Zhaoxia, CHANG, C.S., CHUA, TW, TAN, W.W
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2009
• Subjects: Noise; Ensemble and individual noise reduction; Induction motor; Signature analysis; Stator current.; Databases and Information Systems; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/6856; https://ink.library.smu.edu.sg/context/sis_research/article/7859/viewcontent/2009__Ensemble_and_Individual_Noise_Reduction_Method_for_Induction_motor_Signature_Analysis.pdf
• Institution: Singapore Management University

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.