A Study of Active Noise Cancellation in Ducts

Wang, Chun‐Neng; Tse, Chuan-Cheung; Wen, Cheng

doi:10.1006/mssp.1997.0111

Cited by 12 publications

(3 citation statements)

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“…The application of feedforward compensation in the area of active noise control has received attention in recent years [11][12][13][14][15]. The basic principle and idea behind ANC is to cancel sound by a controlled emission of a secondary opposite (outof-phase) sound signal [16,17]. In most applications, a linearly parametrized filter such as a finite impulse response (FIR) is used for the recursive estimation and adaptation of noise cancellation because of the linear parameter and linear phase shift properties.…”

Section: Active Noise Controlmentioning

confidence: 99%

Filters Parametrized by Orthonormal Basis Functions for Active Noise Control

Zeng

Callafon

2005

Noise Control and Acoustics

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Parametrization of filters on the basis of orthonormal basis functions have been widely used in system identification and adaptive signal processing. The main advantage of using orthonormal basis functions for a filter parametrization lies in the possibility of incorporating prior knowledge of the system dynamics into the identification process and adaptive signal process. As a result, a more accurate and simplified filter with less parameters can be obtained. In this paper, several construction methods of orthonormal basis function are discussed and analyzed. An application of active noise control based on these orthonormal basis constructions is presented.

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Section: Active Noise Controlmentioning

confidence: 99%

Filters Parametrized by Orthonormal Basis Functions for Active Noise Control

Zeng

Callafon

2005

Noise Control and Acoustics

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“…The basic principle and idea behind ANC is to cancel sound by a controlled emission of a secondary opposite (outof-phase) sound signal [5], [6]. Crucial in the active control of sound is.the actual algorithm that generates the controlled emission to obtain sound attenuation.…”

Section: Acta Airduct Silencer Iacated In the System Identification Andmentioning

confidence: 99%

“…It should be noted that the signals in (6) to estimate the feedforward filter F(q,B) are easily obtained by performing a series of two experiments. The first experiment is done without a feedforward compensator, making e ( t ) = H(q)u(t) 4 y ( t ) where e ( t ) is the signal measured at the error microphone.…”

Section: E ( T 0) = H(q)u(t) + F(q @)G(q)u(t)mentioning

confidence: 99%

Feedforward noise cancellation in an airduct using generalized FIR filter estimation

Zeng

Callafon

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475)

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Absfrac-A feedforward control algorithm for active noise control based on the recursive estimation of a generalized finite impulse response (F'IR) filter is presented in this paper.The feedforward control algorithm is applied to a commercial air ventilation silencer to provide active noise compensation in an airduct A generalized FIR filter has the same linear parameter S~N C~U R as a taped delay FIR filter that is favorable for (recursive) estimation purposes. However, the advantage of the generalized FIR fiten lies in the possibility to include prior knowledge of system dynamics in the tapped delay line of the filter. By comparison with a conventional FIR filter implementation it is shnwo that a significant improvement in noise cancellation is obtained.

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Simulations and experiments for hybrid noise control systems

Chen

Too

2009

Applied Acoustics

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A Study of Active Noise Cancellation in Ducts

Cited by 12 publications

References 0 publications

Filters Parametrized by Orthonormal Basis Functions for Active Noise Control

Filters Parametrized by Orthonormal Basis Functions for Active Noise Control

Feedforward noise cancellation in an airduct using generalized FIR filter estimation

Simulations and experiments for hybrid noise control systems

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