An Improved Acoustic Model for Active Noise Control in a Duct

2003 ◽  
Vol 125 (3) ◽  
pp. 382-395 ◽  
Author(s):  
Benjamin J. Zimmer ◽  
Stanley P. Lipshitz ◽  
Kirsten A. Morris ◽  
John Vanderkooy ◽  
Edmund E. Obasi
Keyword(s):  
Transfer Function ◽  
Sound Propagation ◽  
Noise Control ◽  
Active Noise Control ◽  
The Other ◽  
Acoustic Model ◽  
Load Impedance ◽  
Active Noise ◽  
Acoustic Load ◽  
The One

This paper presents a model of sound propagation in a duct, for the purpose of active noise control. A physical model generally different from those explored in much of the literature is derived, with non-constant acoustic load impedance at the one end, and a coupled disturbance loudspeaker model at the other end. Experimental results are presented which validate the derived transfer function.

Active noise control for open windows

2021 ◽  
Vol 263 (3) ◽  
pp. 3097-3107
Author(s):  
Shahin Sohrabi ◽  
Peter Svensson ◽  
Teresa Pàmies Gómez ◽  
Jordi Romeu Garbi
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Sound Intensity ◽  
The Other ◽  
Active Noise ◽  
Open Window ◽  
Pass Through ◽  
Level Reduction ◽  
Suitable Location

Over the last decades, the applications of the active noise control system are broadened. In this study, the active noise control is modeled to reduce the noise pass through an open window. The objective is to define a suitable location for the control sources and error microphones to achieve more noise level reduction at the other side of the window. The performances of the active noise control system are calculated for two different arrangements: (1) the control sources on the edge of the opening and (2) the control sources distributed on the surface of the window. Furthermore, two cost functions are considered to model the noise control system including the minimization of the total squared pressure at cancellation points and the minimization of sound intensity at the surface of the aperture.

EFFECT OF SECONDARY PATH NONLINEARITY IN ACTIVE NOISE CONTROL SYSTEMS BEHAVIOR

2005 ◽  
Vol 05 (02) ◽  
pp. L143-L151 ◽  
Author(s):  
F. TARINGOO ◽  
J. POSHTAN ◽  
M. H. KAHAEI
Keyword(s):  
Transfer Function ◽  
Control Systems ◽  
Noise Control ◽  
Actuator Saturation ◽  
Active Noise Control ◽  
State Behavior ◽  
Statistical Solution ◽  
Acoustic Transducers ◽  
Active Noise ◽  
Saturation Effects

In this paper the behavior of an active noise control system is analyzed considering the nonlinearity of the secondary path transfer function. This nonlinearity may be due to actuator saturation in the operating condition. The statistical solution of the filter weighs adaptation and convergence behavior are obtained. It is shown that the degree of nonlinearity and the error estimation of secondary path transfer function can affect the transient and steady state behavior. The saturation function is considered as a nonlinear system in adaptive filter output. This function models saturation effects in active noise control systems when the acoustic transducers are driven by large-amplitude signals.

scholarly journals Active Noise Control for a Moving Evaluation Point Using Transfer Function Interpolation

2006 ◽  
Vol 49 (3) ◽  
pp. 865-872
Author(s):  
Tomonao OKUYAMA ◽  
Hiroshi MATSUHISA ◽  
Hideo UTSUNO ◽  
Jeong Gyu PARK
Keyword(s):  
Transfer Function ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise ◽  
Evaluation Point

scholarly journals Active noise control for a moving evaluation point considering the change of acoustic transfer function

2018 ◽  
Vol 84 (859) ◽  
pp. 17-00446-17-00446 ◽  
Author(s):  
Kazuya YOKOTA ◽  
Yosuke KOBA ◽  
Satoshi ISHIKAWA ◽  
Shinya KIJIMOTO
Keyword(s):  
Transfer Function ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise ◽  
Evaluation Point ◽  
Acoustic Transfer Function

scholarly journals Active Noise Control for a Moving Evaluation Point Using Transfer Function Interpolation

2005 ◽  
Vol 71 (710) ◽  
pp. 2904-2911 ◽  
Author(s):  
Tomonao OKUYAMA ◽  
Hiroshi MATSUHISA ◽  
Hideo UTSUNO ◽  
Jeong Gyu PARK
Keyword(s):  
Transfer Function ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise ◽  
Evaluation Point

Simulation of Multi-Channel Active Noise Control Based on Dynamic Neural Network

2012 ◽  
Vol 479-481 ◽  
pp. 1293-1296
Author(s):  
Bing Wang ◽  
Ke Ming Zi
Keyword(s):  
Neural Network ◽  
Noise Control ◽  
Active Noise Control ◽  
Time Varying ◽  
Dynamic Neural Network ◽  
Active Noise ◽  
Time Varying Parameters ◽  
Neural Network Algorithm ◽  
The Stability ◽  
The One

The stability of the controller based on traditional adaptive active noise control(AANC) adaptive algorithms is not sufficient because of the time-varying parameters and essential nonlinear property of the active noise control system. The results show that the performance of the controller using multi-channel dynamic neural network algorithm which possess favorable silencing effect and stability is superior to the one using AANC.

Secondary Source Modeling Based on Analogue Circuits of Electrical Mechanical and Acoustical Systems

2011 ◽  
Vol 328-330 ◽  
pp. 2265-2269
Author(s):  
Yong Hong Nie ◽  
Jun Sheng Cheng
Keyword(s):  
Control System ◽  
Transfer Function ◽  
Noise Reduction ◽  
Noise Control ◽  
Active Noise Control ◽  
Secondary Source ◽  
Source Modeling ◽  
Ideal Model ◽  
Active Noise ◽  
Analogue Circuits

A method of secondary source modeling based on analogue circuits of electrical, mechanical and acoustical systems (SSM-ACEMAS) was provided in order to reduce the mismatch of transfer function estimation of secondary path in the simulation of active noise control (ANC) system. The convergence range and noise reduction performance of the system with SSM-ACEMAS and Filtered-X LMS algorithm were investigated. The results show that the transfer function of such a secondary source model has different amplitude and phase from the ideal model, which makes the noise reduction performance of an ANC system be much worse than the one with ideal model. Meantime, the convergence range of the control system is increased at low frequencies while decreased at high frequencies. The proposed model can provide a new method of secondary source modeling for further research on the simulation of active noise control system.

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