Multichannel Active Noise Control System Research Articles

Upgrade of a multi-channel active noise control system for an industrial stack

Active noise control has been studied in the 1990s as an innovative way to reduce the noise in specific situations. Some applications are well known today and found commercial success like noise-canceling headphones. However, the use of active noise control in industrial applications is more complex, thus being an uncommon solution in this field. The use of active noise control for industrial stack noise is one of these applications. One of the first large-scale implementation has been set up at the end of the 1990s. This system was a 10-channel active noise control system installed on a 1.8 m wide chimney to attenuate a 320 Hz pure tone. At that time, an 8 dB noise reduction was achieved at error microphones. Fifteen years later, it has been decided to upgrade the system with the latest generation of digital signal processor (DSP) allowing a real-time optimization and better tracking speed. This paper describes the overall system and the updated multi-channel active noise controller developed for this application. It also presents the improvements, the achieved noise reduction, and the associated environmental benefits.

Convex Combination Filtered-X Algorithms for Active Noise Control Systems

Adaptive filtering schemes exhibit a compromise between convergence speed and steady-state mean square error. Trying to overcome this trade-off, convex combination of adaptive filters have been recently developed for system identification achieving better performance than traditional approaches. The purpose of this work is to apply the convex combination strategy to single-channel and multichannel active noise control systems. In these systems it is necessary to take into account the secondary path between the adaptive filter output and the error sensor and the possible unavailability of the disturbance signal, which depends on the filtering scheme considered. Even though this strategy involves a higher computational burden than the classic adaptive filters, it exhibits a good performance in terms of convergence speed and steady-state mean square error.

A Particle-Swarm-Optimization-Based Decentralized Nonlinear Active Noise Control System

This paper proposes a functional-link-artificial-neural-network-based (FLANN) multichannel nonlinear active noise control (ANC) system trained using a particle swarm optimization (PSO) algorithm suitable for nonlinear noise processes. The use of PSO algorithm in a multichannel ANC environment not only reduces the local minima problem but also removes the requirement of computationally expensive modeling of the secondary-path transfer functions. A decentralized version of a multichannel nonlinear ANC is also developed, which facilitates scaling up of an existing ANC setup without rederiving the learning rules. This is possible as the controller module of each channel is independent of others. Simulation study of the two new multichannel ANC systems demonstrates comparable mitigation performance. However, the decentralized one is preferred to as it possesses the added advantage of scalability.

Co-FXLMS 알고리즘을 이용한 유도전동기의 능동소음제어

In this study, the active noise control experiment has been performed using induction motor noises. While the noises were measured, a induction motor was operated in different speed. For the simulation of ANC(Active Noise Control), test-bed is composed a multi-channel ANC system was constructed. In order to compare the control performance, we performed noise reduction simulations of ANC by Co-FXLMS algorithm and FXLMS algorithm. Through the simulation results, we confirmed that convergence performance and noise decrease effect of the proposed Co-FXLMS algorithm have been improved from existing FXLMS algorithm.

Multi-Channel Active Noise Control System Designs with Fuzzy Logic Stabilized Algorithms

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

능동소음제어를 위한 IIR 구조 2차경로 추정 알고리즘

In this paper, IIR structures are proposed to reduce the computation complexity of the secondary-pass estimation in active noise control(ANC) systems. However, there are stability problems of using IIR models to reduce the computation complexity in ANC systems. To overcome these problems, we propose a stabilizing procedure of recursive least mean squares (RLMS) algorithms for eatimating the parameters of IIR models of the secondary path transfer functions.BR The multichannel ANC systems are implemented by using the TMS320C6713 DSP board to test the performance of computation complexity and stability of the proposed methods. Comparing the IIR filters with the FIR filters, the IIR filters can reduce 50[%] of the computation and obtain similar noise reduction result.

Variable step-size based method for acoustic feedback modeling and neutralization in active noise control systems

This paper investigates the issue of the acoustic feedback during online operation of active noise control (ANC) systems. In the existing approach, two FIR filters are used for this task: adaptive for feedback path modeling (FBPM) and fixed for feedback neutralization (FBN). Previously, a simplified method is proposed where these two tasks of modeling and neutralization have been combined into one feedback path modeling and neutralization (FBPMN) adaptive filter. Here we introduce an intuition based variable step size (VSS) parameter, for LMS equation of FBPMN filter. This VSS is motivated from the fact that the error signal of FBPMN filter contains a disturbance-component that is decreasing in nature. The computer simulations are carried out for single-channel and multichannel ANC systems. It is demonstrated that the proposed method achieves better performance than the existing methods.

624 多チャンネル波形同期法を用いたANCの基礎研究

It is strongly required to reduce noise at moving person's ears in a noisy room by some active noise control (ANC) techniques. In the case of using fixed secondary sources, some multi-channel control methods are necessary. Various methods have been proposed for this on-line system identification, but it takes time to identify the error paths and the system can't follow quick movement of the error microphones, in the case of multi-channel system. On the other hand, Wave Synthesis (WS) Method is only useful for periodic noises, for example, purr of engines and tones of fans. But the feature of this algorithm is not to need the system identification of the error path. When error point moves, this algorithm can follow it. The single channel WS method has been developed and applied to purr of engines so far and has obtained great noise reduction. However, a multi-channel system using WS algorithm has not been established. According to these backgrounds, the final target of this research is to develop multi-channel WS ANC system and apply it to reduce noise at person's ears who move in a noisy room with periodic sound. In this report, at, first, we deduced multi-channel Wave Synthesis Algorithm. Next, we performed the experiment in the single channel system and checked convergence time. Consequently, it's confirmed that high order harmonics components decrease quickly. In addition we checked how quick to follow movement of the error microphone.

Multichannel active control of tonal fan noise in laptops.

A multichannel active noise control system, based on a feed forward LMS algorithm, is simulated and implemented experimentally to reduce tonal noise components from internal cooling fans in laptops. Several 3-D simulations were carried out in order to determine the proper number and location of sensors and actuators, with three different criteria of reduction: sound pressure, sound intensity at discrete points, and global sound power. Results of simulations show reductions of up to 38 dB in the radiated sound power for a configuration consisting of three control actuators, three error sensors, and one reference sensor. Subsequently, experimental tests were undertaken of active noise control in a laptop, with the proposed configuration, in an anechoic chamber. Results show reductions of up to 15 dB in the sound pressure levels of individual error sensors. Hence, it is concluded, both theoretically and experimentally, that active noise control is a promising strategy to reduce tonal fan noise in personal computers.

Multichannel Filtered Inverse LMS Algorithm for ANC: Laboratory Implementation and Testing

This paper describes the development and implementation of a filtered-inverse least-mean-square (FILMS) algorithm for a multichannel active noise control system (ANCS). The FILMS algorithm is derived from the well-known filtered-x LMS (FXLMS) algorithm with the aim of improving the rate of convergence and reducing the considerable computational load of the multichannel FXLMS algorithm. Mathematical development and equations describing the multichannel FILMS algorithm are presented in the first part of this paper and the laboratory setup and techniques used to implement and test FILMS-based ANCS are described in the second part. Results of the implemented system are presented and discussed.

A simplified method for online acoustic feedback path modeling and neutralization in multichannel active noise control systems

The presence of strong acoustic feedback degrades the performance of active noise control (ANC) systems, and in the worst case the ANC system may become unstable. In this paper, we investigate additive-random-noise-based methods for online feedback path modeling and neutralization (FBPMN) in multichannel ANC systems. In existing methods, separate filters are used for each acoustic feedback path: one for online feedback path modeling (FBPM), and another for feedback path neutralization (FBPN). Furthermore, the existing method works well for predictable noise sources but its performance degrades for unpredictable sources. This paper attempts to solve these problems in multichannel ANC systems. The proposed method is a modification and extension of previous work for online FBPMN in single-channel ANC systems. In the proposed method, we combine the two tasks of FBPM and FBPN in one online FBPMN filter, and hence, the computational complexity of the proposed method is lower than existing methods. Computer simulations are carried out to demonstrate the effectiveness of the proposed method. It is shown that the proposed method achieves better performance than existing methods for both predictable and unpredictable noise sources. Furthermore, this improved performance is achieved at somewhat reduced computational complexity.

APPLICATION OF GENETIC ALGORITHMS FOR OVERALL OPTIMIZATION OF AN ACTIVE NOISE CONTROL SYSTEM IN AN ENCLOSURE

One of the main important aspects in designing an active control system is the optimization of position and number of sensors and actuators. In this paper this problem is addressed for the implementation of a multi-channel active noise control (ANC) system with the aim of global reduction of broadband noise in a telephone kiosk. This includes optimizing the locations for loudspeakers and microphones, finding proper size of the control system, i.e. the number of loudspeakers and microphones, and optimization of the control signals. The mean of acoustic potential energy in the enclosure in a frequency range of 50 Hz to 300 Hz is selected as the performance index for optimization purpose. Several genetic algorithms are proposed and compared to find the global minimum of this performance index. In order to have a better performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and the best genetic algorithm is selected among them. The main difference between the proposed algorithms is the used coding scheme. Numerical simulations of the acoustical potential energy and also sound pressure at the height where the head of a person may be located, confirms the optimality of the locations proposed by the genetic algorithm.

Online secondary path modeling in multichannel active noise control systems using variable step size

In single-channel feedforward active noise control (ANC) systems, additive random noise based methods are often applied to achieve secondary path modeling (SPM) during online operation. This paper investigates the issue of online SPM in multichannel ANC systems. It is shown that the application of existing methods for online SPM in multichannel ANC systems greatly increases the computational complexity. Here we extend our previous work on single-channel variable step-size online SPM to multichannel ANC systems. It is shown that the proposed method has reduced computational complexity as compared with other methods. Computer simulations are carried out that demonstrate the effectiveness of the proposed method.

The influences of path characteristics on multichannel feedforword active noise control system

In this paper, a new analysis method for the performance of multiple channel feedforward active noise control (ANC) system in frequency domain is proposed. The reference paths from original sources to reference sensors and the secondary paths are considered when reference sensors cannot be installed close to the original sources. A closed expression of eigenvalues of spectral density matrix is given to determine the fixed step size. The convergence performance of the ANC algorithm is analyzed in detail, and the result shows that the reference paths and the secondary paths determined by the position of the reference sensors, loudspeakers and error sensors are the main factors to the final performance. Four impulse responses measured in a real laboratory are used in the simulations to verify the conclusions.

Pseudo-Affine Projection Algorithms for Multichannel Active Noise Control

For feedforward multichannel active noise control (ANC) systems, the use of adaptive finite-impulse response (FIR) filters is a popular solution, and the multichannel filtered-x least-mean-square (FX-LMS) algorithm is the most commonly used algorithm. The drawback of the FX-LMS is the slow convergence speed, especially for broadband multichannel systems. Recently, some fast affine projection algorithms have been introduced for multichannel ANC, as an interesting alternative to the FX-LMS algorithm. They can provide a significantly improved convergence speed at a reasonable additional computational cost. Yet, the additional computational cost or the potential numerical instability in some of the recently proposed algorithms can prevent the use of those algorithms for some applications. In this paper, we propose two pseudo-affine projection algorithms for multichannel ANC: one based on the Gauss-Seidel method and one based on dichotomous coordinate descent (DCD) iterations. It is shown that the proposed algorithms typically have a lower complexity than the previously published fast affine projection algorithms for ANC, with very similar good convergence properties and good numerical stability. Thus, the proposed algorithms are an interesting alternative to the standard FX-LMS algorithm for ANC, providing an improved performance for a computational load of the same order

Multichannel active noise control system without secondary path models using the simultaneous perturbation algorithm

This paper presents a novel multichannel active noise control (ANC) system without secondary path models. This ANC system uses a simultaneous perturbation algorithm as the updating algorithm and has an advantage that secondary path models (estimation of secondary paths) are not required, unlike the MEFX (multiple error filtered-X)-based ANC. This system can consequently control noise stably because there are not modeling errors that cause system instability. The computational complexity is also very small. Experimental results demonstrate that the proposed multi-channel ANC system can operate stably under the environment where the error microphones always move.

DESIGN OF DECOUPLING ACTIVE NOISE CONTROL SYSTEMS

In this paper a simple method for multi-channel Active Noise Control (ANC) is introduced. The proposed structure is a combination of an adaptive FIR filter, based on the FXLMS algorithm, and the ALIGN algorithm resulting in a decoupled matrix for secondary path transfer function. This structure thus converts a multi-channel ANC system to decoupled systems which results in the reduction in computational load without affecting the convergence behavior of the FXLMS system.

The Gauss‐Seidel fast affine projection algorithm for multichannel active noise control and sound reproduction systems

AbstractIn the field of adaptive filtering, the fast implementations of affine projection algorithms are known to provide a good tradeoff between convergence speed and computational complexity. Such algorithms have recently been published for multichannel active noise control systems. Previous work reported that these algorithms can outperform more complex recursive least‐squares algorithms when noisy plant models are used in active noise control systems. This paper proposes a new fast affine projection algorithm for multichannel active noise control or sound reproduction systems, based on the Gauss–Seidel solving scheme. The proposed algorithm has a lower complexity than the previously published algorithms, with the same convergence speed and the same good performance with noisy plant models, and a potential for better numerical stability. It provides the best performance/cost ratio. Details of the algorithm and its complexity are presented in the paper, with simulation results to validate its performance. Copyright © 2004 John Wiley & Sons, Ltd.

D05: A portable active noise control system

The paper presents a portable multichannel active noise control (PANC) system destined for creation of spatial zones of quiet in enclosures. PANC is an autonomous analog input/output system with 8 analog input channels for reference and error microphones, and 8 analog output channels for control loudspeakers. PANC is controlled by Renesas SH4 CPU with a 240 MHz clock aided for data processing by Spartan 2E FPGA. It may process data with the maximum sampling frequency 100kHz. In the paper details of hardware as well as software solutions are described.

Optimal configurations for active control of axial fans

The minimum power radiated from a single monopole noise source surrounded by four symmetrically spaced control sources has been shown analytically. A similar analysis has also been completed for a monopole noise source surrounded by three symmetrically spaced control sources. At Brigham Young University, a multichannel active noise control system has been developed for a small axial cooling fan employing four symmetrically spaced miniature loudspeakers as control actuators. This arrangement of control loudspeakers has exhibited good global control of the fan’s tonal noise, achieving close to the predicted ideal for some harmonics of the blade passage frequency. According to theory, a three-source control configuration should be able to achieve nearly the same power reduction as a four-source configuration. While this is so, increasing the number of control sources to greater than four gives little to no increase in predicted power attenuation. A three-source control implementation, then, appears to be a comparable solution for the fan noise control problem. The experimental results of a three-source control and fan configuration will be discussed. An assessment will be made of the three- and four-source arrangements, including also a comparison of the experimental results versus the theoretical ideal.