An efficient method to regularize reference signal for ANC system

Chen, K; Paurobally, R; Pan, J; Qiu, X

An efficient method to regularize reference signal for ANC system

Chen, K Paurobally, R Pan, J Qiu, X

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Publication Type:: Conference Proceeding
Citation:: 21st International Congress on Sound and Vibration 2014, ICSV 2014, 2014, 6 pp. 4870 - 4877
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Chen, K	en_US
dc.contributor.author	Paurobally, R	en_US
dc.contributor.author	Pan, J	en_US
dc.contributor.author	Qiu, X https://orcid.org/0000-0002-5181-1220	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	21st International Congress on Sound and Vibration 2014, ICSV 2014, 2014, 6 pp. 4870 - 4877	en_US
dc.identifier.isbn	9781634392389	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121133
dc.description.abstract	In this paper, an improved algorithm for active control of fan noise is proposed. The main idea behind this work is to optimize the components in the reference signal using the information from the unwanted fan noise. In the algorithm, the linear prediction coefficients obtained from the noise is used to build an autoregressive model. Then the model is applied to the reference signal to improve the correlation between the regularized reference signal and the noise. This reference signal regularization (RSR) is carried out automatically by an adaptive autoregressive process. The RSR improves the control performance noticeably. The algorithm has a fast convergence rate and high stability with a tolerant increase in computational complexity. It was implemented to reduce the noise from a real fan on a digital signal processor.	en_US
dc.relation.ispartof	21st International Congress on Sound and Vibration 2014, ICSV 2014	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	An efficient method to regularize reference signal for ANC system	en_US
dc.type	Conference Proceeding
utslib.citation.volume	6	en_US
utslib.for	091301 Acoustics and Noise Control (excl. Architectural Acoustics)	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	6	en_US

Abstract:

In this paper, an improved algorithm for active control of fan noise is proposed. The main idea behind this work is to optimize the components in the reference signal using the information from the unwanted fan noise. In the algorithm, the linear prediction coefficients obtained from the noise is used to build an autoregressive model. Then the model is applied to the reference signal to improve the correlation between the regularized reference signal and the noise. This reference signal regularization (RSR) is carried out automatically by an adaptive autoregressive process. The RSR improves the control performance noticeably. The algorithm has a fast convergence rate and high stability with a tolerant increase in computational complexity. It was implemented to reduce the noise from a real fan on a digital signal processor.

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http://hdl.handle.net/10453/121133