SIMULATION OF ACTIVE NOISE CONTROL IN ENCLOSURES USING DIRECT SOUND FIELD PREDICTION

2009 ◽  
Vol 17 (01) ◽  
pp. 83-107 ◽  
Author(s):  
CHRISTOPHER G. PROVATIDIS ◽  
SPIRIDON T. MOUZAKITIS ◽  
GEORGE N. CHARALAMPOPOULOS
Keyword(s):  
Boundary Conditions ◽  
Noise Control ◽  
Active Noise Control ◽  
Sound Field ◽  
New Method ◽  
Test Case ◽  
Sensors And Actuators ◽  
Sound Fields ◽  
Secondary Sources ◽  
Active Noise

This paper is concerned with the active control of sound fields in enclosures. Specifically, the numerical problem of determining the optimum locations of control sensors and actuators is addressed. A new method for determining the optimum secondary sources strength is proposed, based on the explicit prediction of the sound field, which makes the simulation of realistic acoustical applications feasible, in terms of the enclosure's boundary conditions. The irregular geometry of a car cabin with complex boundary conditions is used in order to demonstrate the application of the new method to a test case where the existing methods cannot theoretically apply without resolving to significant numerical error. The new method of determining the secondary sources strength is combined with a modified genetic and a gradient optimization algorithm so as to locate the optimum positions of active noise control transducers for global sound field control. The overall algorithm, constituting of the method for calculating the secondary sources' strength and the optimization algorithms, is adjusted with computational improvements for better performance.

scholarly journals Noninvasive Model Independent Noise Control with Adaptive Feedback Cancellation

2008 ◽  
Vol 2008 ◽  
pp. 1-7 ◽  
Author(s):  
Jing Yuan
Keyword(s):  
Boundary Conditions ◽  
Noise Control ◽  
Reference Signal ◽  
Active Noise Control ◽  
Sound Field ◽  
Path Modeling ◽  
Feedback Cancellation ◽  
Sound Fields ◽  
Path Models ◽  
Model Independent

An active noise control (ANC) system is model dependent/independent if its controller transfer function is dependent/independent on initial estimates of path models in a sound field. Since parameters of path models in a sound field will change when boundary conditions of the sound field change, model-independent ANC systems (MIANC) are able to tolerate variations of boundary conditions in sound fields and more reliable than model-dependent counterparts. A possible way to implement MIANC systems is online path modeling. Many such systems require invasive probing signals (persistent excitations) to obtain accurate estimates of path models. In this study, a noninvasive MIANC system is proposed. It uses online path estimates to cancel feedback, recover reference signal, and optimize a stable controller in the minimum H2 norm sense, without any forms of persistent excitations. Theoretical analysis and experimental results are presented to demonstrate the stable control performance of the proposed system.

scholarly journals Optimization of Secondary Sources Configuration in Two-Dimensional Space Based on Sound Field Decomposition and Sparsity-Inducing Regularization

2019 ◽  
Vol 37 (4) ◽  
pp. 697-703
Author(s):  
Kean Chen ◽  
Jian Xu ◽  
Lei Wang ◽  
Bing Zhou
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Noise Control ◽  
Dimensional Space ◽  
Active Noise Control ◽  
Sound Field ◽  
Optimization Methods ◽  
Secondary Sources ◽  
Active Noise ◽  
Configuration Information

During the design of transducers configuration for an active noise control system, current optimization methods need to predetermine the error sensors configuration, which significantly increases the workload of later optimization of the secondary sources configuration. In this study, a new method free from specific error sensors configuration information is presented that higher order microphones are used to capture the sound field so as to formulate the cost function in wave domain. In addition, according to sparsity characteristics of the primary sound field, sparsity-inducing regularization is introduced to optimize the secondary sources configuration, including the number and positions, by calculating a sparse approximate solution to underdetermined equations. Effects of the number of candidate secondary sources are discussed, and the comparison with the uniform configuration and the optimized configuration using the genetic algorithm is performed. Results show that the proposed method can optimize the secondary sources configuration effectively independent of the error sensors configuration information. The noise reduction of the proposed method is close to that by the genetic algorithm, while other evaluation metrics for the system are much better, which would benefit the stability of active noise control system.

Role of Acoustic Properties in Biomedical Active Noise Control

2020 ◽  
Vol 9 (1) ◽  
pp. 48-60
Author(s):  
Sajil C. K. ◽  
Achuthsankar S. Nair
Keyword(s):  
Numerical Simulation ◽  
Biomedical Applications ◽  
Noise Control ◽  
Active Noise Control ◽  
Acoustic Properties ◽  
Reflection Coefficients ◽  
Sensors And Actuators ◽  
Active Noise ◽  
Source Signal

Active noise control (ANC) systems are tailored for user-specific scenarios which are required in biomedical applications due to the physical restrictions in the placement of sensors and actuators. This study examines the role of spectral flatness of acoustic channels and room reflection coefficients in ANC performance. Each room has a unique characteristic response in transforming a source signal. By employing preliminary measurements and numerical simulation, the authors show that improved noise control is possible by optimizing room reverberation and spectral flatness of the secondary acoustic channel. This result has potential application in improving existing ANC systems in biomedical applications like fMRI.

Active noise control in a pure tone diffuse sound field using virtual sensing

2009 ◽  
Vol 125 (6) ◽  
pp. 3742-3755 ◽  
Author(s):  
D. J. Moreau ◽  
J. Ghan ◽  
B. S. Cazzolato ◽  
A. C. Zander
Keyword(s):  
Pure Tone ◽  
Noise Control ◽  
Active Noise Control ◽  
Sound Field ◽  
Active Noise ◽  
Virtual Sensing

scholarly journals Directional Active Noise Control with a Local Minimax Error Criterion

2019 ◽  
Vol 9 (19) ◽  
pp. 4065
Author(s):  
Kexun Chi ◽  
Ming Wu ◽  
Rong Han ◽  
Chen Gong ◽  
Jun Yang
Keyword(s):  
Noise Control ◽  
Mean Squared Error ◽  
Active Noise Control ◽  
Quadratic Function ◽  
Sound Field ◽  
Control Area ◽  
Error Criterion ◽  
Active Noise ◽  
Directional Control ◽  
Nelder Mead Algorithm

The traditional mean squared error (MSE) criterion can be formulated as a quadratic function of a vector of control filter coefficients, and it is easy to obtain optimal control filter coefficients. Although the MSE criterion can lead to noise reductions in the control area, an unpredictable directional residual sound field is generated. In this paper, we propose a method for multi-channel active harmonic noise control with a local minimax error criterion based on the Nelder–Mead algorithm, which leads to reductions at all error positions and greater reductions at controllable positions. Directional noise reduction experiments of two areas are presented for two different error criteria at discrete locations in an anechoic chamber. Compared with a system employing the traditional MSE criterion, the results show that an active noise control system with the proposed criterion can achieve extra reductions at specified locations and overall noise reductions at the same time. The present research offers some important insights into directional control.

103 2-channel active noise control in three dimensional sound field

2006 ◽  
Vol 2006 (0) ◽  
pp. 5-6
Author(s):  
Toshihiko Higashi ◽  
Shinya Kijimoto ◽  
Yoichi Kanemitu ◽  
Koichi Matuda ◽  
Ikuma Ikeda ◽  
...  
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Sound Field ◽  
Active Noise

I24 2-channel active noise control in three dimensional sound field

2006 ◽  
Vol 2006.59 (0) ◽  
pp. 251-252
Author(s):  
Toshihiko Higashi ◽  
Yoichi Kanemitu ◽  
Shinya Kijimoto ◽  
Koichi Matuda
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Sound Field ◽  
Active Noise

Noise Reduction in Ducts Achievable by Point Control

1998 ◽  
Vol 120 (2) ◽  
pp. 216-223 ◽  
Author(s):  
K. A. Morris
Keyword(s):  
Noise Reduction ◽  
Closed Loop ◽  
Noise Control ◽  
Active Noise Control ◽  
Practical Interest ◽  
Noise Levels ◽  
Sensors And Actuators ◽  
One Dimensional ◽  
Active Noise ◽  
Point Control

Noise control in a one-dimensional duct is analyzed. This problem is of practical interest and is also simple enough that a complete theoretical analysis is possible. It is shown that the optimal controller leads to an unstable closed loop. The noise reduction level achievable with a stable closed loop is calculated for arbitrary choices of sensor and actuator locations. This enables the best placement of sensors and actuators to be determined. Also, the analysis indicates that a “spatial waterbed” effect exists in some configurations of active noise control: i.e., that noise levels are increased for points outside of the region over which the design is done.

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