Active Noise Control System Research Articles

Development and Testing of an Active Noise Control System for Urban Road Traffic Noise

As urbanization accelerates, the increasing number of vehicles and travel demands contribute to escalating road traffic noise pollution. Although passive noise control techniques such as noise barriers and green belts effectively mitigate noise, they occupy urban space, exacerbating the scarcity and high cost of already congested city areas. Emerging as a novel noise reduction strategy, active noise control (ANC) eliminates the need for physical isolation structures and addresses the noise within specific frequency ranges more effectively. This paper investigates the characteristics of urban road traffic noise and develops an ANC prototype. Utilizing the Least Mean Squares (LMS) algorithm, we conduct active noise control tests for various types of single- and dual-frequency noise within the prototype’s universal platform to validate its actual noise reduction capabilities. The study demonstrates that urban road traffic noise is mostly in the mid- to low-frequency range (below 2000 Hz). The developed ANC prototype significantly reduces single- or dual-frequency noise within this range, achieving a maximum noise reduction of nearly 30 dB(A). Future research should expand noise reduction tests across more frequency bands and assess the noise reduction effectiveness against real road traffic noise.

A survey on filtered-x least mean square-based active noise control systems with emphasis on reducing computational complexity

Active noise control (ANC) is gaining ever-increasing attention owing to its powerful ability to attenuate low-frequency noise. The computational complexity of an ANC system may directly affect its computational efficiency, control performance, and hardware costs. Therefore, the focus of this paper is mainly on discussing the development of ANC systems with emphasis on reducing computational complexity. The ANC systems are classified into two groups of narrowband and broadband systems. The computational complexity analysis is provided to show the computational merit of each system with respect to the conventional ANC systems. In addition, numerical simulations are performed to evaluate the convergence speed and noise reduction performance of the considered systems. The results show that, in the narrowband ANC systems, the LFE-NANC, CFX-NANC and BFX-NANC systems enjoy better overall performance in terms of the computational complexity, convergence speed and steady-state error, and in the broadband ANC systems, the DF-BANC system has the lowest computational complexity but cannot effectively attenuate the broadband noise with high spectral dynamics, whereas the DS-BANC and MDS-BANC systems can. This study provides in-depth insight into current typical low-complexity ANC systems.

Development of Giant Magnetostrictive Materials for an Active Noise Control System in an Ultracompact Electric Vehicle

Recently, ultracompact electric vehicles (EVs) have begun to be sold, instead of general vehicles equipped with gasoline engines, for transportation. However, because the outer plate of an ultracompact EV has low rigidity, the road noise generated by rotation and the wind noise generated from the vehicle's projection shape are transmitted to the inside of the EV. This interior noise reduces the ride comfort for passengers. Therefore, an active noise control (ANC) system was proposed for controlling noise transmitted from the outside of the EV. The proposed ANC system was configured to control the sound generated using a giant magnetostrictive actuator on the wall surface in the cabin of the EV, instead of a vehicle installation speaker.In this study, Tb, Dy, and Fe powders, which are giant magnetostrictive materials, were mixed and mechanically alloyed to produce multiple giant magnetostrictive materials to be used in the proposed ANC system. The displacement of each alloyed giant magnetostrictive material was measured. In addition, each alloyed material was analyzed using X-ray diffraction and their crystal orientation was confirmed.

An efficient offline scheme to compute an FIR controller for active reduction of acoustic reflections in an anechoic chamber

This paper presents an offline iterative scheme to efficiently obtain a fixed controller for larger-scale active noise control systems. The approach reduces the computational complexity of the scheme by applying preconditioning and prewhitening via the frequency domain, followed by conversion of the filters to the time domain using the inverse Fourier transform. Although the filters are not necessarily causal, causality is ensured by utilizing delay and truncation techniques. The use of these filters in the iterative scheme leads to improved convergence, lowering computational effort while also being memory efficient. Regularization is applied to maintain convergence while allowing for larger step sizes between iterations. The controller minimizes the reflected sound field, which is measured by the performance sensors. The signals of the performance sensors are computed with the Kirchhoff–Helmholtz integral. The results show that this allows for global control of the reflected sound field within the microphone area. A simulation is shown of a noise control setup with 12 primary sources, 12 secondary sources, 12 reference sensors, 12 error sensors and 37 performance sensors. Although the delay of the filters in the direct path is reflected in the filter coefficients, this delay can be truncated to obtain filter coefficients without any delay. Despite the truncation resulting in an average loss in performance of 1.6 dB, the control system without any delays is able to reduce the average reflected sound at the performance sensors by 13.8 dB, when the reference signal is known.

An augmented diffusion algorithm with bidirectional communication for a distributed active noise control system.

Recent studies on diffusion adaptation for distributed active noise control (DANC) systems have attracted significant research interest due to their balance between computational burden and stability compared to conventional centralized and decentralized adaptation schemes. The conventional multitask diffusion FxLMS algorithm assumes that the converged solutions of all control filters are consistent to each other, which is unrealistic in practice hence results in inferior performance in noise reduction. An augmented diffusion FxLMS algorithm has been proposed to overcome this problem, which adopts a neighborhood-wide adaptation and node-based combination approach to mitigate the bias in the converged solution of the multitask diffusion algorithms. However, the improvement comes at the expense of a higher computational burden and communication cost. All existing DANC systems, including the multitask and augmented diffusion algorithms, assume one-way communication between nodes. By contrast, this paper proposes a bidirectional communication scheme for the augmented diffusion algorithm to further reduce the memory requirement, computational burden, and communication cost. Simulation results in the free field and with measured room impulse responses both demonstrate that the proposed augmented diffusion algorithm with bidirectional communication can achieve a faster convergence speed than that based on one-way communication with a lower memory, computation, and communication burden.

An adaptive algorithm for acoustic feedback compensation and secondary path identification of an active noise control system.

An adaptive variable step-size algorithm is proposed in this paper to address the impact of the real-time acoustic feedback and the real-time secondary path identification on the overall noise reduction performance of an active noise control system. An automated adjustment weight factor is introduced in the algorithm to accelerate the convergence of the acoustic feedback path as well as the secondary path identification, and to prevent possible system divergence. It is shown in this study that the proposed algorithm can resolve the trade-off between a fast convergence and a low misalignment of the virtual and the actual control paths typically found in conventional algorithms. An optimized control structure is also proposed in the study by enabling an adaptive gain adjustment based on the output of the auxiliary filter to enhance the practicality of the control system. The effectiveness of the algorithm is tested using two simulated multi-component signals and a broadband noise signal, and the results confirm that the proposed algorithm can achieve a good noise reduction with only a few iterations.

Experimental evaluation of feedforward active noise control system with optical laser microphone and proportional-integral-differential filter

In this paper, we propose a feedforward active noise control (ANC) system with an optical laser microphone utilizing a proportional-integral-differential (PID) filter. The feedforward ANC system with the optical laser microphone has been proposed to relax the causality constraint. This system adopts a first-order differentiator to modify the velocity picked up by the optical laser microphone. This modification achieves the improvement of the coherence between the velocity as the reference signal and the unwanted noise as the sound pressure. However, the frequency response of the first-order differentiator is similar to the high-pass filter and attenuates the reference signal at low frequencies. This causes the degradation of the noise reduction performance of the conventional ANC system. To solve this problem, the proposed ANC system adopts the PID filter instead of the first-order differentiator. By adjusting the coefficients of the PID filter, the proposed system avoids the attenuation of the reference signal at low frequencies. Then, the noise reduction performance can be improved. Experimental results show that the proposed ANC system reduces the unwanted noise compared to the conventional ANC system and relaxes the causality constraint compared to the basic ANC system in the real-time operation.

Investigation of Effect of Mean Flow on Active Noise Control System in Duct

The increasing demand for a quieter living environment has driven the development of noise reduction and control technologies. Previous research has demonstrated the significant impact of mean flow on the performance of noise reduction devices. While efforts have been made to enhance passive noise control systems in the presence of mean flow, research on the influence of mean flow on active noise control (ANC) systems is limited, particularly in terms of computational modeling. This study addresses this gap by investigating the effect of mean flow on ANC system performance using a validated virtual controller within a computational framework, complemented by experimental investigations. The acoustic propagation inside the computational domain is computed using the Computational Aeroacoustics method, and the ANC system is modeled using FxLMS algorithm with the virtual-controller method as proposed in our earlier work. Through experiments, it reveals that the presence of mean flow in duct reduces the performance of the ANC system. The numerical investigation exhibited a consistent trend in line with the experimental findings, showing a strong agreement between the 3D numerical simulations and experimental data. These numerical results offer compelling evidence that the computational framework used in this study accurately models the impact of mean flow on ANC systems.

A robust auxiliary noise power scheduling strategy for online secondary path modeling in active noise control systems

Auxiliary noise injected in active noise control (ANC) systems for online secondary path modeling (SPM) contributes to the residual noise, and thus deteriorates the noise control performance of ANC systems. Moreover, sudden changes in secondary path may lead to easy divergence of the existing online SPM methods. This paper improves the existing methods from three aspects to further mitigate these problems: 1) the noise power is varied on the basis of the convergence status of SPM filter so that large-power noise is injected at the start or when secondary path changes and the power is reduced as the filter converges. 2) a novel ON/OFF controlling strategy is used in the method so that the noise injection is suspended at the optimum point when the modeling accuracy is sufficient. 3) continuous check for error outliers is applied in the method to detect changes in secondary path so that the injection of noise can be reactivated in the case of path perturbation. Comparative simulations show the effectiveness of the improved method both in convergence and noise reduction performance. In addition, the improved method is robust against sudden changes in secondary path.

Active noise control with variable directivity loudspeakers

Active noise control (ANC) is an effective way to reduce the low frequency noise level for passengers in cars or aircrafts. In these applications, secondary sources are usually monopole loudspeakers. Variable directivity loudspeaker is a kind of loudspeaker which is able to control its own radiation directivity. It is potential to be able to control the sound field better compared monopole loudspeaker. Inspired by this, variable directivity loudspeakers are applied to an ANC system. A simulation is conducted to investigate the performance of the ANC system with variable directivity loudspeakers. Simulation results show that the ANC system with variable directivity loudspeakers outperforms the one with monopole loudspeakers in noise control using the same number of loudspeakers.

CRNN-based spatial active noise control in spherical harmonics domain

In this work, an active noise control (ANC) in the spherical harmonics (SH) domain, along with a learning model, is developed. The traditional ANCs are built on the adaptive signal processing framework and fail in the presence of nonlinear distortions. Further, these algorithms are limited to the horizontal plane only. In contrast, the proposed work develops the ANC in the 3D space using the SH representation with the spherical microphone array (SMA) as the error microphone. The SH decomposition calculates the SH pressure coefficients from the SMA recordings. Subsequently, a convolutional recurrent neural network (CRNN) is trained to estimate the real and imaginary spectrograms from the SH coefficients as the input features. The output of the CRNN is the canceling signal that eliminates or attenuates the primary noise in the ANC system. A delay-compensated method addresses ANC system latency. According to simulations and experiments, the proposed learning-based spatial ANC reduces wideband noise and generalizes to untrained noises.

Active Noise Control for Kitchen Hood

A kitchen hood is an appliance that is powered by a fan motor to suck the exhaust in the kitchen while cooking. When turned on, it produces low-frequency noise that cannot be reduced by only a passive material. There is a direct relationship between the speed settings in the hood and in the amount of noise that is produced. The higher the speed setting, the higher the noise. This broadband noise is reduced using the filtered-x least mean square (FXLMS) method with a feedforward active noise control (ANC) structure. To ensure a good reduction, the microphones must have good coherence and must not be affected by the turbulent wind. The whole ANC system will use one reference microphone, several error microphones connected as one, and two anti-noise speakers connected as one.

Simultaneous perturbation algorithm for active noise control with an asynchronous wireless microphone

This paper investigates the issues on the use of an asynchronous wireless microphone in an active noise control (ANC) system. In a previous work, the jitter effect of the wireless error microphone is addressed by adopting the simultaneous variable perturbation (SVP) algorithm to update the control filter of the ANC system. However, another critical issue has been overlooked. The wireless microphone can have a different sampling rate from that of the ANC controller, because the analog-to-digital convertors for the ANC controller and the wireless microphone are triggered by separate crystal oscillators. This may deteriorate the convergence performance of the ANC system. In this paper, the simulation results demonstrate that both the SVP and online secondary path modeling (OSPM) algorithms are not affected by the sampling rate of the wireless error microphone, when the sampling rate difference is less than 0.01%. However, the sampling rate difference of the wireless reference microphone can lead to about 7 dB and 5 dB degradations in the noise reduction performance of the SVP and OSPM algorithms, respectively.

Frequency domain online secondary path modelling for active noise control without auxiliary noise

The identification of the secondary path transfer function is of vital importance for active noise control (ANC) system. Online secondary path modeling method is preferable to offline modeling due to its tracking capability in time-varying acoustic environments. However, the auxiliary noise of online modeling mixed with the residual error signal diminishes the noise control performance. In this paper, we propose a frequency domain online secondary path modelling algorithm based on our previous work which achieves simultaneous acoustic paths modeling and noise control without auxiliary noise. The uniqueness of the solution is theoretically analyzed, and the computational burden is shown significantly lower than the previously proposed method. Simulations are conducted to verify that the proposed algorithm also has a better convergence behavior.

Efficiency testing of active noise control in the duct outlet and effect of the error microphone location

In a duct, the performance of the active control system depends among other things on the position of the loudspeaker. In ventilation systems, they are usually inserted in the ductwork along the duct wall or in the duct if its diameter is large enough not to generate too much pressure drop. In this paper, we describe an active noise control system placed not in the duct but at its outlet, instead of the ventilation grille. The control loudspeaker being no longer in the duct, it must remain close enough to the outlet to "colocalize" the two sources of sound waves (ventilation noise and control) and keep a global noise control while leaving a sufficiently large opening to allow a similar ventilation flow obtained with a standard ventilation mouth. The error microphone is placed outside the duct and the influence of its position is also analyzed on a ventilation system prototype. The obtained attenuation is good and extends over a wider range of frequencies than when the loudspeaker is placed at the periphery of the duct. Moreover, its position at the outlet of the duct is better for using the speaker as a source of sound diffusion.

Coherence between error and acoustic reference microphones with two closely located noise sources

It is well known that locating acoustic reference microphones near the error microphone can improve the coherence between reference and error signals in feedforward active noise control systems. In this paper, the effects of the number of reference microphones and the distance between noise sources and reference microphones on the coherence between the reference and error signals are investigated based on an analytical model. Two scenarios when the two noise sources are located on the same side or opposite sides of the error microphone are studied. The simulation results show that the coherence coefficient can reach 1.0 regardless of the distance between the noise sources and the reference microphones if the number of reference microphones is the same as that of the noise sources. When the number of reference microphones is less than that of noise sources, the coherence coefficient in the low frequency range decreases as the reference microphones move close to the noise sources.

Hybrid Active Noise Control with Auxiliary Filter-based Virtual Sensing

In this paper, we propose a hybrid active noise control system with auxiliary filter-based virtual sensing. The proposed system consists of a Feed-Forward (FF) part, which can reduce broadband noise, and a FeedBack (FB) part, which can reduce narrowband disturbance components, by introducing virtual sensing into the hybrid ANC. Virtual sensing is realized by using two auxiliary filters because the optimal noise control filters are different for the FF and FB parts, respectively. These auxiliary filters store information on the optimal noise control filters that can reduce both narrowband disturbance and broadband noise at the desired location in the tuning stage. Through simulations with real impulse responses for real applications, we demonstrate that the proposed hybrid ANC can achieve an overall noise reduction of about 30 dB.

An analysis of a feedback active noise control system using the remote microphone technique

This paper examines strategies in virtual sensing feedback active noise control systems and compares the noise reduction performance of three strategies: using physical microphones for direct feedback control, using virtual microphones for direct feedback control, and using physical microphones for indirect virtual feedback control. For a primary sound field with incident waves in a single direction, simulation results indicate that employing a physical microphone for indirect virtual feedback control consistently yields superior noise reduction performance than that using a physical microphone for direct feedback control. However, if the causal requirement between physical and virtual microphones is not satisfied, the increase in the equivalent secondary path delay deteriorates noise reduction performance while utilizing physical microphones for indirect virtual feedback control. For a primary sound field containing waves from multiple directions, the simulation results show that the noise reduction performance is affected by both the coherence and causality between the physical and virtual microphone signals.

Variation of the secondary acoustic paths from loudspeakers at the seat shoulder in an automobile cabin

The secondary path is essential in the design of adaptive active noise control systems, and it varies with several factors in practical implementation. In this paper, the acoustic responses from secondary loudspeakers installed at the shoulder of the front passenger seat to the error microphones at the passenger's ears in an automobile cabin are measured, when the factors including the passenger movement, the seat posture and the passenger number change. The upper limit frequency where the phase variation is within 90 deg. compared to the reference position is analyzed. The results show that the state of both the passenger head and the seat back determines the lowest upper limit frequency among all the factors under investigation. If multiple factors change at the same time, the upper limit frequency will be further reduced.

A Modified Simultaneous Perturbation Stochastic Approximation Algorithm for Active Noise Control

Secondary path modeling is an important step in active noise control. Keeping the active noise control system stable, when the secondary path changes over time, is a widely studied problem. Using the simultaneous perturbation stochastic approximation algorithm, can update the control filter without secondary path modeling, avoiding the problem of increased noise caused by secondary path modeling. In this paper a variant of the simultaneous perturbation stochastic approximation algorithm is proposed, which incorporates historical coefficients of the control filter, to correct the direction of the gradient calculation. Based on an experimental setup with a realistic transfer path, this paper demonstrates that the proposed algorithm has superior performance in terms of convergence speed and noise reduction amount, than the general simultaneous perturbation stochastic approximation algorithm.