Ensemble and individual noise reduction method for induction-motor signature analysis
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 denoisingm...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2009
|
| Subjects: | |
| 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 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
|---|