Two Step Optimization of Transducer Locations in Single Input Single Output Tonal Global Active Noise Control in Enclosures

2010 ◽  
Vol 132 (6) ◽  
Author(s):  
J. Ignacio Palacios ◽  
Jordi Romeu ◽  
Andreu Balastegui
Keyword(s):  
Control System ◽  
Active Control ◽  
Acoustic Field ◽  
Noise Control ◽  
Active Noise Control ◽  
Single Input Single Output ◽  
Secondary Sources ◽  
Single Output ◽  
Active Noise ◽  
Single Input

Global active control of sound can be achieved inside enclosures under low modal acoustic fields. However, the performance of the system depends largely on the localization of the elements of the control system. For a purely acoustic active control system in which secondary acoustic sources (loudspeakers) and pressure transducers (microphones) as error sensors are used, several optimization strategies have been proposed. These strategies usually rely on partial approximation to the problem, focusing on the study of number and localization of secondary sources without considering error transducers, or selecting the best positions of secondary sources and error transducers of an initial set of candidate locations for these elements. The strategy presented here for tonal global active noise control of steady states comprises two steps; the first is rather common for this sort of problem and its goal is to find the best locations for secondary sources and their strengths by minimizing the potential energy of the enclosure. The second step is the localization of the error transducer, which ensures the results of the first step. It is analytically demonstrated that for a single input single output system, the optimum location of error transducers is at a null pressure point of the optimally attenuated acoustic field. It is also shown that in a real case, the optimum position is that of a minimum of the optimally attenuated acoustic field. Finally, a numerical validation of this principle is carried out in a parallelipedic enclosure.

THEORETICAL ANALYSIS OF SEMI-ACTIVE NOISE CONTROL

Akustika ◽  
2021 ◽  
pp. 152
Author(s):  
Thomas Kletschowski
Keyword(s):  
Active Control ◽  
Noise Control ◽  
Control Volume ◽  
Active Noise Control ◽  
Broadband Noise ◽  
Electrical Network ◽  
Single Input Single Output ◽  
Single Output ◽  
Active Noise ◽  
Single Input

significant reduction of disturbing noise can be achieved by passive, semi-active and fully active control approaches. Passive noise treatments such as dynamic vibration absorber are very robust and can be applied to obtain a broadband performance. Active noise control systems are designed to control harmonic or broadband noise. They are very effective, if the control volume is small as known from single-input/single-output systems used in active headphones. However, if distributed control is required, the control profit is not scalable, because the required multiple-input/multiple output systems must be adjusted to specific acoustic modes as known from the active control of propeller-aircraft interior noise. Semi-active control that is based on the principle of dissipation allows to combine several single-input/single-output systems without coupling. Thus semi-active approaches are capable to solve the problem of scalability. The present paper reports on a specific approach that is based on a dynamic absorber attached to a vibrating structure and coupled with a dissipating electrical network. The electrical components of this network can be adjusted to the mechanical impedance to realize dissipation. To focus on the performance principle, the theoretical investigations are presented in a dimensionless analysis.

Adaptive Feedforward Active Noise Control in an Acoustic Duct

2001 ◽  
Author(s):  
A. R. Ohadi ◽  
E. Esmailzadeh ◽  
A. Alasty
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Superior Performance ◽  
Single Input Single Output ◽  
Single Output ◽  
Active Noise ◽  
Input Signals ◽  
Single Input ◽  
Simulation Results ◽  
Adaptive Feedforward

Abstract The single-reference/multi-output active noise control (ANC) of an accurate physical model of an acoustic duct system has been investigated. Computer model of a multi-channel ANC system with tonal and sweep sine input signals, and an adaptive feedforward algorithm that minimizes the generic cost function are developed. Results obtained for various single-input/single-output (SISO) configurations of ANC systems were compared. The dynamic response of a single-reference/multi-output ANC system, using Minimax and MEFXLMS algorithms, is studied and the effect of acoustical feedback neutralization in a multichannel ANC system is studied. Simulation results demonstrate that the multi-channel adaptive feedforward ANC system, using the Minimax algorithm, has a superior performance in comparison to the same system with MEFXLMS.

scholarly journals Design of Self-Tuning Minimum Effort Active Noise Control with Feedback Inclusion Architecture

2009 ◽  
Vol 28 (3) ◽  
pp. 205-215 ◽  
Author(s):  
R. K. Raja Ahmad ◽  
M. O. Tokhi
Keyword(s):  
Noise Control ◽  
Transfer Functions ◽  
Controller Design ◽  
Active Noise Control ◽  
The Self ◽  
Recursive Least Squares ◽  
Single Input Single Output ◽  
Single Output ◽  
Active Noise ◽  
Self Tuning

This paper presents the development of a self-tuning controller design of minimum effort active noise control (ANC) for feedforward single-input single-output (SISO) architecture which includes the feedback acoustic path in the controller formulation. The controller design law is derived for suitable self-tuning implementation and the self-tuning controller is evaluated in a realistically constructed ANC simulation environment. The self-tuning controller design involves a two-stage identification process where the controller is replaced by a switch. This switch is closed and opened in sequence generating two transfer functions which are then used in constructing the controller specified by a minimum effort control law. The implementation requires an estimate of the secondary path transfer function which can be identified either online or offline. The controller design and implementation are evaluated in terms of the level of cancellation at the observer through simulation studies for various values of modified effort weighting parameter in the range 0 ≤ γ ≤ 1. It was found that the optimal controller designed using this technique which is constrained only by the accuracy of the two models identified using recursive least squares algorithm, yields good cancellation level.

Active Control of High Order Acoustical Modes in a Semi-Infinite Waveguide

1991 ◽  
Vol 113 (4) ◽  
pp. 523-531 ◽  
Author(s):  
J. D. Stell ◽  
R. J. Bernhard
Keyword(s):  
Control Systems ◽  
Active Control ◽  
Noise Control ◽  
Active Noise Control ◽  
High Order ◽  
Control Methods ◽  
Control Performance ◽  
Secondary Sources ◽  
Active Noise ◽  
New Finding

This paper presents an analysis of the effectiveness of active noise control methods for control of high order modes in rigid-walled, semi-infinite waveguides. The waveguides examined in this investigation are terminated at one end with a rigid end. The case studies performed reconfirmed that n control actuators can control n propagating modes (including the plane wave) in a waveguide if the actuators are properly placed. The results also confirmed that the control actuators should be located at the node surfaces of the most significant evanescent modes to avoid various problems that evanescent modes cause active control systems. A significant new finding is the effect of the rigid waveguide termination on the active controller. The reflected energy from the termination causes standing waves in the region between the rigid termination and the secondary sources. At certain frequencies which correspond to resonant conditions, the standing wave amplitudes become large and the control actuator strength must be high. At these frequencies the effects of the evanescent modes become significant even when the mode is not close to its cut-on frequency. Similar resonant effects can be expected to affect active noise control performance for any case where there are significant reflections in the waveguide upstream of the control actuators.

Simulation of Active Noise Control System on the Truck Interior Cab

2013 ◽  
Vol 798-799 ◽  
pp. 443-447
Author(s):  
Qi Chen LU ◽  
Hui Bin LI ◽  
Hua Huang
Keyword(s):  
Control System ◽  
Control Systems ◽  
Active Control ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Frequency Noise ◽  
Simulink Model ◽  
Active Noise ◽  
Active Control System

Studying on adaptive active noise control (AANC) system of the truck interior cab to reduce the low-frequency noise,a normalization FLMS algorithm simulink model is established in Matlab/Simulink.Then taking it as the core,a feedforward adaptive active control system and a feedback adaptive active control system of the tuck interior cab are established in Matlab/Simulink .Considerating the actual error channels effects on systems ,the noise reduction effects of two adaptive active control systems are verified from the simulintion results.Through comparing the two wo adaptive active control systems,we found that the feedforward adaptive active control system is more stable.

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.

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