Modal parameters identification of power transformer winding based on improved Empirical Mode Decomposition method

Electric Power Systems Research

Volumn 108, Issue , 2014, Pages 331-339

  Geng, Chao ^a   Wang, Fenghua ^a   Zhang, Jun ^a   Jin, Zhijian ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Empirical Mode Decomposition; Masking signal; Modal parameter identification; Power transformer; Winding

Indexed keywords

EMPIRICAL MODE DECOMPOSITION; EMPIRICAL MODE DECOMPOSITION METHOD; ENSEMBLE EMPIRICAL MODE DECOMPOSITIONS (EEMD); IMPROVED EMPIRICAL MODE DECOMPOSITIONS (EMD); MASKING SIGNALS; MODAL PARAMETER IDENTIFICATION; MODAL PARAMETERS IDENTIFICATION; TRANSFORMER MANUFACTURING;

COMPOSITE BEAMS AND GIRDERS; EXPERIMENTS; MODAL ANALYSIS; SIGNAL PROCESSING; TRANSFORMER WINDINGS; VIBRATION ANALYSIS; WINDING;

POWER TRANSFORMERS;

EID: 84891505759     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.epsr.2013.12.002     Document Type: Article

References (20)

1. S. Borucki Diagnosis of technical condition of power transformers based on the analysis of vibroacoustic signals measured in transient operating conditions IEEE Transactions on Power Delivery 27 2012 670 676
2. B. García, J.C. Burgos, and Á. Alonso Winding deformations detection in power transformers by tank vibrations monitoring Electric Power Systems Research 74 2005 129 138 (Pubitemid 40245128)
3. H.K. Li, Y. Li, and X.H. Yu Axial vibrations modal analysis and computation of power transformer windings under different levels of pre-compression Electric Machines and Control 14 2009 98 101
4. P.S. Georgilakis, M.A. Tsili, and A.T. Souflaris A heuristic solution to the transformer manufacturing cost optimization problem Journal of Materials Processing Technology 181 2007 260 266 (Pubitemid 44468173)
5. P.S. Georgilakis, and E.I. Amoiralis Spotlight on transformer design IEEE Power and Energy 5 2007 40 50 (Pubitemid 46104043)
6. P.S. Georgilakis Condition monitoring and assessment of power transformers using computational intelligence International Journal of Electrical Power and Energy Systems 33 2011 1784 1785
7. P.S. Georgilakis, J.A. Katsigiannis, K.P. Valavanis, and A.T. Souflaris A systematic stochastic petri net based methodology for transformer fault diagnosis and repair actions Journal of Intelligent and Robotic Systems 45 2006 181 201
8. S.C. Ji, J.D. Wang, and Y.M. Li Research on axial vibration characteristics of transformer windings under steady condition Advanced Technology of Electrical Engineering and Energy 25 2006 35 38
9. Y. Li, W. Zhou, Y. Jing, and X. Sun Axial vibration analysis of power transformer active part under short-circuit IEEE International Conference on Electrical Machines and Systems (ICEMS) 2011 1 4
10. T. Nagata, and K. Hirai Estimation on on-load vibration of transformer windings IEEE on Power Engineering Society Winter Meeting 2002 1378 1382 (Pubitemid 34669340)
11. S.R. Ibrahim, and E.C. Mikulcik A method for the direct identification of vibration parameters from the free response Shock and Vibration Bulletin 47 1977 183 198
12. B. Peeters, and G. De Roeck Reference-based stochastic subspace identification for output-only modal analysis Mechanical Systems and Signal Processing 13 1999 855 878 (Pubitemid 30515442)
13. B. Peeters, H. Van der Auweraer, P. Guillaume, and J. Leuridan The PolyMAX frequency-domain method: a new standard for modal parameter estimation Shock and Vibration 11 2004 395 409
14. J.N. Yang, Y. Lei, S. Pan, and N. Huang System identification of linear structures based on Hilbert-Huang spectral analysis. Part 1: normal modes Earthquake Engineering & Structural Dynamics 32 2003 1443 1467 (Pubitemid 36971761)
15. N.E. Huang, Z. Shen, and S.R. Long et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 454 1998 903 995 (Pubitemid 128733183)
16. Z. Wu, and N.E. Huang Ensemble empirical mode decomposition: a noise-assisted data analysis method Advances in Adaptive Data Analysis 1 2009 1 41
17. S.Q. Qin, Q.H. Pu, and Z. Shi A method of modal parameters identification using ambient vibration measurement for a large scale bridge Journal of Vibration and Shock 31 2012 95 100
18. R. Deering, and J.F. Kaiser The use of a masking signal to improve empirical mode decomposition IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005. Proceedings (ICASSP'05) 2005 485 488
19. H.Q. Ying, J.M. Liu, and S. Shen Half-power bandwidth method and INV damping ration solver study Noise and Vibration Control 2 2006 4 6
20. W.P. Hu, and M.H. Du The limitation of sampling for the empirical mode decomposition Signal Processing 23 2007 637 640