Study on Nonlinear Problem of Active Noise Control System for Power Transformers

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Abstract:

With the development of active noise control technology, ANC system has been gradually introduced into practical application. And some researches and experiments notice that ANC system may encounter with nonlinearity problems under certain conditions in practical applications. The paper analyses and summarizes possible factors that may lead to nonlinearity problems, based on the operation principle and structure features of ANC system, and classifies the main methodologies of dealing with nonlinearity problems considering the main technologies and researches nowadays of system nonlinearity with the same analyzing structure of nonlinearity factors mentioned in the paper. The paper also elaborates the strength and weakness of different methodologies and the most appropriate application condition for each methodology, and it provides theoretical basis for nonlinear active noise control system.

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4106-4110

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February 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Li Tan, Jean Jiang. Adaptive Volterra Filters for Active Control of Nonlinear Noise Processes[J]. signal processing, 2001, Vol. 49: 1667-1676.

DOI: 10.1109/78.934136

Google Scholar

[2] T. Matsuura, T. Hiei, H. Itoh, and K. Torikoshi. Active noise control by using prediction of time series data with a neural network[C]. in Proc. IEEE SMC Conf, 1995, vol. 3.

DOI: 10.1109/icsmc.1995.538084

Google Scholar

[3] W. Klippel, Active attenuation of nonlinear sound. U.S. Patent 6 005 952, Dec. 21, (1999).

Google Scholar

[4] P. Strauch and B. Mulgrew. Active control of nonlinear noise processes in a linear duct[J]. IEEE Trans. on Signal Processing, 1998, 46(9): 2404-2412.

DOI: 10.1109/78.709529

Google Scholar

[5] M. Bouchard, B. Paillard, and C.T.L. Dinh. Improved training of neural networks for the nonlinear active control of sound and vibration[J]. IEEE Trans. on Neural Networks, 1999, 10(2): 391-401.

DOI: 10.1109/72.750568

Google Scholar

[6] D.P. Das and G. Panda. Active mitigation of nonlinear noise processes using a novel filtered-s LMS algorithm[J]. IEEE Trans. On Speech and Audio Processing, 2004, 12(3): 313-322.

DOI: 10.1109/tsa.2003.822741

Google Scholar

[7] I.J. Leontaritis and S.A. Billings. Input-output parametric models for non-linear systems - Part I: deterministic non-linear systems[J]. Int. J. of Control, 1985, 41(2): 303-328.

DOI: 10.1080/0020718508961129

Google Scholar

[8] H. Zhao, X. Zeng, and J. Zhang. Adaptive reduced feedback FLNN filter for active control of nonlinear noise processes[J]. Signal Processing, 2009, 90(3): 834-847.

DOI: 10.1016/j.sigpro.2009.09.001

Google Scholar