Time-frequency analysis of DC bias vibration of transformer core on the basis of Hilbert–Huang transform

This paper presents a time–frequency analysis of the vibration of transformer under direct current (DC) bias through Hilbert–Huang transform (HHT). First, the theory of DC bias for the transformer was analyzed. Next, the empirical mode decomposition (EMD) process, which is the key in HHT, was introduced. The results of EMD, namely, intrinsic mode functions (IMFs), were calculated and summed by Hilbert transform(HT) to obtain time-dependent series in a 2D time–frequency domain. Lastly, a test system of vibration measurement for the transformer was set up. Three direction (x, y, and z axes) components of core vibration were measured. Decomposition of EMD and HHT spectra showed that vibration strength increased, and odd harmonics were produced with DC bias. Results indicated that HHT is a viable signal processing tool for transformer health monitoring.

[1]  Helmut Pfützner,et al.  Rise-of-temperature method for building factor distribution in 1-phase model transformer core interior considering high DC bias , 2014 .

[2]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[3]  L. Matakas,et al.  Transformer Operation at Deep Saturation: Model and Parameter Determination , 2010, IEEE Transactions on Industry Applications.

[4]  A.R. Messina,et al.  Assessment of nonlinear interaction between nonlinearly coupled modes using higher order spectra , 2005, IEEE Transactions on Power Systems.

[5]  Jung-Pyo Hong,et al.  Comparative Study of Stator Core Composition in Transverse Flux Rotary Machine , 2011 .

[6]  Wang Kun.  Simulative Study on Power Transformer With DC Magnetic Biasing , 2009 .

[7]  V. Vittal,et al.  Characterization of nonlinear modal interaction using normal forms and Hilbert analysis , 2004, IEEE PES Power Systems Conference and Exposition, 2004..

[8]  Arturo Roman Messina,et al.  ANALYSIS OF INTER-AREA OSCILLATIONS VIA NON-LINEAR TIME SERIES ANALYSIS TECHNIQUES , 2005 .

[9]  U. Madawala,et al.  The Effect of DC Bias Conditions on Ferrite Core Losses , 2008, IEEE transactions on magnetics.

[10]  V. Vittal,et al.  Analysis of higher order terms for small signal stability analysis , 2005, IEEE Power Engineering Society General Meeting, 2005.

[11]  S. S. Shen,et al.  A confidence limit for the empirical mode decomposition and Hilbert spectral analysis , 2003, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[12]  Yuesheng Xu,et al.  Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum , 2006 .

[13]  Guo Lei.  Test and Simulation for Single-phase Transformer Under DC Bias , 2007 .

[14]  A.R. Messina,et al.  Identification of instantaneous attributes of torsional shaft signals using the Hilbert transform , 2004, IEEE Transactions on Power Systems.

[15]  Robert X. Gao,et al.  A tour of the hilbert-huang transform : An empirical tool for signal analysis , 2007 .

[16]  Yong Cheol Kang,et al.  Estimation of the Separate Primary and Secondary Leakage Inductances of a Y-Δ Transformer Using Least Squares Method , 2010 .