Blind Equalization of Partial Discharge Channels

Keywords: partial discharge, signal analysis, blind equalization, decorrelation, direct signal, reflected signal, superposition

Abstract


Abstract. In the case of partial discharge signals, obtained during "on-line" monitoring or "off-line" tests of the generator, there is often interference between the direct and reflected signals or disturbances during propagation through the medium, i.e. the structure that transmits the pulse of partial discharges to the measuring terminal or detector. The paper describes the application of the method of "blind equalization" of the partial discharge signal transmission channel, which was shown to be able to be used to extract the direct signal of partial discharges in case of overlap with reflected signals through decorrelation of direct and reflected signals. The term "blind equalization" reflects the ignorance of the characteristics of the channel (transmission medium) and they should be computationally "separated" from the composite signal on the detector.

References

N. Kartalovic, D. Kovacevic and S.Milosavljevic, “An Advanced Model of Partial Discharge in Electrical Insulation“, Facta Universitatis (Nis), Ser.: Elec. Energ. vol. 24, no. 1, April 2011, 43-57 https://doi.org/10.2298/FUEE1101041K

J. Chan, H. Ma, and T. Saha, "Automatic blind equalization and thresholding for partial discharge measurement in power transformer," IEEE Trans. Power Del., Vol. 29, pp. 1927-1938, 2014. doi: 10.1109/TPWRD.2014.2322114.

H. Zhang, T. Blackburn, B. Phung, and D. Sen, “A novel wavelet transform technique for on-line partial discharge measurements Part 1: WT de-noising algorithm,” IEEE Trans. Dielectr. Electr. Insul., vol. 14, pp. 3–14, Feb. 2007. doi: 10.1109/TDEI.2007.302864

X. Zhou, C. Zhou, and I. Kemp, “An improved methodology for application of wavelet transform to partial discharge measurement denoising,” IEEE Trans. Dielectr. Electr. Insul., vol. 12, pp. 586–594, Jun. 2005. doi: 10.1109/TDEI.2005.1453464

G. Luo, D. Zhang, Y. Koh, K. Ng, and W. Leong, “Time–frequency entropy-based partial-discharge extraction for nonintrusive measurement,” IEEE Trans. Power Del., vol. 27, pp. 1919–1927, Oct. 2012. doi: 10.1109/TPWRD.2012.2200911

J. Chan, H. Ma, T. Saha, and C. Ekanayake, “Self-adaptive partial discharge signal de-noising based on ensemble empirical mode decomposition and automatic morphological thresholding,” IEEE Trans. Dielectr. Electr. Insul., vol. 21, pp. 294–303, Feb. 2014. doi: 10.1109/TDEI.2013.003839.

J. Chan, H. Ma, T. Saha, and C. Ekanayake, “A novel level-based automatic wavelet selection scheme for partial discharge measurement,” in Australasian Universities Power Eng. Conf., Bali, Indonesia, 2012, pp. 1–6.

B. Jelonnek, D. Boss, and K. Kammeyer, “Generalized eigenvector algorithm for blind equalization,” Signal Process., vol. 61, pp. 237–264, Sep. 1997 https://doi.org/10.1016/S0165-1684(97)00108-4

O. Shalvi and E. Weinstein, “New criteria for blind deconvolution of nonminimum phase systems (Channels),” IEEE Trans. Inf. Theory, vol. 36, pp. 312–321, Mar. 1990. https://doi.org/10.1109/18.52478

Published
2024/04/04
Section
Professional Paper