Research on PD Signals Denoising Based on EMD Method

• Autorzy: Pei Y. , Wu Y. , Jia D.

Warianty tytułu

PL

Badania odszumiania sygnału wyładowania niezupełnego bazujące na metodzie empirycznej dekompozycji EMD

• Języki publikacji: EN

Abstrakty

EN

Adaptive decomposition of complex data is realized and intrinsic mode function (IMF) components that reflect different scales information are gained through empirical mode decomposition (EMD) of partial discharge (PD) signals. The gained intrinsic mode function components are reconstructed after the wavelet threshold processing to reduce the interference of noise. This partial discharge signals denoising method has achieved good effect in the processing of simulation and measured data, which proves the effectiveness and superiority of the method.

PL

Przedfstawionbo metode adaptacyjnej dekompozycji danych złożonych na przykładzie sygnału wyładowania niezupełnego. Do usunięcia wpływu szumów wykorzystano analizę falkową.

Słowa kluczowe

EN

partial discharge; empirical mode decomposition; intrinsic mode function

PL

wyładowanie niezupełne; rozkłady empiryczne; wewnętrzna funkcja trybu

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 1b
• Strony: 137--140
• Opis fizyczny: Bibliogr. 17 poz., rys., wykr.

Twórcy

autor

Pei Y.

autor

Wu Y.

autor

Jia D.

• College of GeoExploration Science and Technology, Jilin University, Changchun, 130026, China,

Bibliografia

• [1] Guo J., Wu G.N., Zhang X.Q., The Actuality and Perspective of Partial Discharge Detection Techniques, Transaction of China Electrotechnical Society., 20(2005), No. 2, 29-35
• [2] Xiao Y., Yu W.Y., Research on Waveform Matching Recognition Algorithm in Partial Discharge Pulse Extraction, Transaction of China Electrotechnical Society., 20(2005), No. 5, 87-91
• [3] Xu J., Huang C.J., Jin H., Algorithm for Extracting PD Signals Based on a Wavelet-set, Automation of Electric Power Systems., 28(2004), No. 16, 36-40
• [4] Sun C.X., Li X., Yang Y.M., The Method of Drawing the PD Signals from White Noise by Wavelet Analysis., Transaction of China Electrotechnical Society., 14(1999), No. 3, 47-50
• [5] Zhong Y.M., QIN S.R., Research on the Uniform Theoretical Basis for Hilbert-Huang Transform, Journal of Vibration and Shock., 25(2006), No.3, 40-43
• [6] Zhu., Shen Z., Eckermann S.D., Gravity Wave Characteristics in the Middle Atmosphere Derived from the Empirical Mode Decomposition Method, Geophysical Research., 102(1997), No.14, 545-561
• [7] Nunes J.C., Niang O., Bouaoune Y., Bidimensional Empirical Mode Decomposition Modified for Texture Analysis, Scandinavian Conference on Image Analysis., 2003, 171-177
• [8] Song L.X., GAO F.J., XI Z.H., Compared and Improved Research of Bidimensional Empirical Mode Decomposition Method, Journal of Electronics & Information Technology., 30(2008), No. 12, 2890-2893
• [9] Huang N.E., Wu M.C., Long S.R., A Confidence Limit for the Empirical Mode Decomposition and Hilbert Spectral Analysis, Proceedings of the Royal Society A., 459(2003), 2317-2345
• [10] Song P.J., Zhang J., The Application of Two-Dimensional EMD to Separating Contents of Oceanic Remote Sensing Images, High Technology Letters., 9(2001), 62-67
• [11] Huang N.E., Wu Z.H., A Study of the Characteristics of White Noise Using the Empirical Mode Decomposition Method, Proceedings of the Royal Society., 460(2004), 1597-1611
• [12] Yu D.J., Cheng J.S., Yang Y., Application of EMD Method and Hilbert Spectrum to the Fault Diagnosis of Roller Bearings, Mechanical Systems and Signal Processing., 19(2005), No.2, 259-270
• [13] Judd M.D., Cleary G.P., Bennoch C.J., Power Transformer Monitoring Using UHF Sensors: Site Trials, Proceedings of the 2006 IEEE International Symposium on Electrical Insulation., 2006, 145-149
• [14] Raja K., Devaux F., Lelaidier S., Recognition of Discharge Sources Using UHF PD Signatures, IEEE Electrical Insulation Magazine., 18(2007), No.5, 8-14
• [15] Downier T.R., Silverman B.W., The Discrete Multiple Wavelet Transform and Thresholding Methods, IEEE Trans on Signal Processing., 46(1998), No.9, 2558-2561
• [16] Satishl., Nazneen B., Wavelet-Based Denoising of Partial Discharge Signals Buried in Excessive Noise and Interference, IEEE Trans on Dielectrics and Electrical Insulation., 10(2003), No.2, 354-367
• [17] Qian Y., Huang C.J., Chen C., Denoising of Partial Discharge Based on Empirical Mode Decomposition, Automation of Electric Power Systems., 29(2005), No. 12, 53-60