Study of Blind Source Separation on Transmission Line EMI

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Abstract:

The transmission line is an important part of electrical system. Electromagnetic interference (EMI) signals can be picked up by transmission lines in a way of conduction or radiation, and interfere the sensitive devices located in the power source end and the load end, so it is important and necessary to separate and identify the EMI source signals coupling to the transmission lines in order to guide the electromagnetic compatibility (EMC) design and the further EMI diagnosis and suppression. Fast independent component analysis (FastICA) algorithm is studied and programmed, and its feasibility and separation performance are validated via simulation of BSS of three mixed signals and the average signals to interference ratio (SIR) is approximately 30 dB. The model of crosstalk of transmission lines is built and simulated, the interference signals are separated by the FastICA algorithm, and the average SIR is over 20 dB. Periodicity and spectral characteristics of the separated interference signals are analyzed, and the identification of interference signals is realized.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

493-499

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Online since:

November 2013

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] X. Yu and D. Hu: Theory and Application of Blind Source Separation (Science Press, China 2011).

Google Scholar

[2] A. Hyvärinen, J. Karhunen and E. Oja: Independent Component Analysis (Publishing House of Electronics Industry, China 2007).

Google Scholar

[3] X. Shi: Blind Signal Processing - Theory and Practice (Shanghai Jiaotong University Press, China 2008).

Google Scholar

[4] S. H. Hall and H. L. Heck: Advanced Signal Integrity for High-Speed Digital Designs (Publishing House of Electronics Industry, China 2011).

Google Scholar

[5] B. Le, M. Shao and J. Huang: Principles and Applications of Pattern Recognition (Xi'an University of Electronic Science and Technology Press, China 2008).

Google Scholar