Feedforward Active Noise Control Research Articles

A Feedback Active Control Approach to Road Noise Based on a Single Microphone Sensor to Improve Automotive Cabin Sound Comfort.

Tire-road noise deteriorates the sound quality of a vehicle's interior and affects the driving safety and comfort. Obtaining low interior noise is a challenge for passenger car manufacturers. Traditional passive noise control (PNC) is efficient for canceling high frequency noise but not useful for low frequency noise, while active noise control (ANC), according to the residual error signal, can generate an anti-noise signal to reduce the original noise. Most research has focused on improving the control effect for a feedforward ANC system. However, this paper emphasizes a feedback ANC system based on a signal microphone sensor. There are two main contributions in this study to improve automotive cabin sound comfort. One is that the algorithm of the feedback ANC system using a single microphone sensor without a reference noise signal is proposed based on the Filtered-x Least Mean Square method. The other is that the algorithm applies additive random noise online to estimate the secondary path model. A simulation was implemented based on measured real road noise data, and the simulation results indicate that the proposed feedback ANC system with the single microphone sensor can effectively attenuate road noise. This study shows the feasibility of applying a feedback ANC system in automobiles to increase the cabin sound quality.

A semi-adaptive feedforward hybrid active noise control algorithm for multichannel systems.

Broadband active noise control systems incorporating fixed controllers exhibit limited ability to reduce sinusoids. This study presents a semi-adaptive feedforward hybrid active noise control (HANC) system to address this issue. The proposed system pairs fixed high-order optimal controllers for broadband noise with adaptive low-order FXLMS-based controllers for narrowband noise. Notably, parallel broadband and narrowband controllers work independently. The proposed semi-adaptive feedforward HANC system demonstrates low computational complexity which makes it suitable for multichannel systems. Simulations and experiments validate the effectiveness of the proposed system in controlling mixed noise.

A scalable hybrid analog-digital architecture for multi-channel feedforward active noise control

This paper proposes a hybrid analog-digital architecture, aimed at reducing hardware resource consumption and improving the scalability of a multi-channel feedforward active noise control system to accommodate a large number of error microphones. This hybrid architecture employs a partial-update filtered-x least mean squares algorithm that is lightweight and suitable for real-time execution, as it updates the control filters in each iteration using only two selected error signals. The selection of these two error signals is achieved through a dedicated analog circuit comprising analog comparators and multiplexers. Thus, the hybrid architecture requires only two analog-to-digital converters for error signals, regardless of the number of error microphones. Experiments were conducted on two active noise control casings, demonstrating that, with a specific computational capacity, the proposed hybrid architecture can accommodate significantly longer control filters, resulting in higher steady-state noise reduction. Moreover, additional error microphones were introduced to demonstrate the scalability. The hybrid architecture simplifies the implementation of the multi-channel feedforward active noise control system when additional error microphones are needed for more evenly distributed residual noise levels or a larger zone of quiet.

An improved stability compensation for feedforward active noise control systems with acoustic feedback

An improved stability compensation for feedforward active noise control systems with acoustic feedback

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.

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.

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.

Theoretical convergence analysis of the FXLMS-based feedforward hybrid active noise control system

Real noise typically includes both broadband and narrowband components, such as noise generated by rotating machines. The feedforward hybrid active noise control (FFHANC) system reduces both components separately by arranging broadband and narrowband controllers in parallel. Although considerable efforts have been made to improve the FFHANC system, a theoretical analysis of its performance is still lacking. Consequently, the application of the FFHANC system lacks a solid foundation. Furthermore, the stability bounds of step sizes that guarantee convergence are not available in the literature. To address these problems, a convergence analysis of the FFHANC system based on the filtered-x least-mean-square algorithm is proposed. The analysis of the mean and mean-square convergence behaviors of the weight errors theoretically illustrates the advantages of the FFHANC system in terms of fast convergence and high reduction. The mutual coupling of parallel controllers in the mean-square sense is derived and discussed. By predicting the steady-state mean-square error and stability bounds, the proposed model can also guide the choice of step sizes. Our analysis lays the theoretical foundation for the practical application of the FFHANC system. Extensive simulations are performed to demonstrate the validity of the proposed theoretical theory.

Active control of impulsive scattered sound based on virtual sensing

Active control method is an important way to reduce the scattered radiation of 3D objects and render them acoustically invisible. Traditional active control requires the error sensor to be sufficiently close to the target area because the zone of quiet (ZoQ) is generated around the sensor; thus, the scattered noise cannot be eliminated at the remote position in situations wherein the microphone can only be placed near the scatterer. To solve this dilemma, this study proposed two methods of predicting and controlling the scattered sound, combined with adaptations of two commonly used virtual sensing (VS) methods: the auxiliary-filter-based virtual-sensing (AF-VS) and the remote microphone technique (RMT). Both methods are based on the correlation between signals to predict the scattered noise; therefore, ZoQ can be transferred to the non-near-field target position with fewer physical microphones. Further, the causal constraints need not be satisfied in the former method, which uses pre-trained auxiliary filters to implicitly estimate and control the scattered pressure at the target point. Whereas, the latter explicitly estimates the scattered component instead of the total sound pressure with the pre-modeled observation matrix, thereby avoiding the causality limitation of the RMT and reducing one estimation process. Experiments were conducted to suppress impulsive scattered sound using a dual-channel feedforward adaptive ANC system, and the attenuation performances of the two proposed methods were compared with those of the direct control of the desired noise with the optimal Wiener solution and the method without combining the VS. The results demonstrated the feasibility and effectiveness of the two active control methods for scattered sound using virtual sensors. Moreover, in the impulsive scattered sound control with a 300 Hz-1000 Hz carrier, the average noise reduction (NR) at the observation points reached approximately 18 dB, and a more stable and excellent performance was obtained using the latter method based on RMT. Therefore, this research provides a solution for the case of limited error sensor placement in scattered sound active control systems; and in addition, can be used to guide the choice of VS methods in scattered sound control applications.

The Predict and Invert Feedback Active Noise and Vibration Control Algorithm

This work proposes an algorithm for feedback ANC that does not require a prior secondary path model and usually remains stable after fast secondary path changes, as other algorithms proposed for feedforward ANC. This is achieved using a recursive least squares algorithm to model the secondary path and the primary noise with an autoregressive moving average model. The resulting model allows for predicting future values of the primary noise. Finally, the primary noise values predicted are filtered by a non-causal inverse of the secondary path model to generate the anti-noise signal. Simulation results attest to the validity of the algorithm in reducing narrowband noise.

A Complete Design of Smart Pad That Reduces Snoring

This paper presents integration of active noise control (ANC) systems with a smart pad to reduce the noise made by snoring. One reference microphone, two secondary speakers and two error microphones are used with a feedforward ANC algorithm in the smart pad design. Several smart functions including snore detection, quiet zone localization, and advanced audio integration are proposed. An effective way to satisfy the causality constraint of the feedforward ANC system is presented. The smart pad is independent of the pillow and is not in contact with the user; it is portable and is not a burden to the user during sleep. Several experiments are conducted to confirm the effectiveness of the smart pad when used on a full-size bed.

Stability Guaranteed Active Noise Control: Algorithms and Applications

Stability of the controller, robust stability of the active noise control (ANC) system, and limited output power of the hardware control board or actuators are crucial issues for ANC applications. Violation of these requirements results in output saturation, and hence nonlinear distortion by overloading the actuators. As a consequence, noise reduction performance of an ANC system will be dramatically degraded. A novel frequency-weighted leaky filtered-x least-mean-square (FxLMS) algorithm is developed in this article to fulfill these requirements. The proposed algorithm is an improvement of the traditional leaky FxLMS algorithm, where a frequency-weighted matrix is designed to replace the corresponding scalar weight. The frequency-weighted matrix, which is achieved by solving a constrained optimization problem, consists of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\it N$</tex-math> </inline-formula> frequency-weighted factors. By the frequency-weighted factors, the frequency response of the control filter is only suppressed at specific frequencies where the requirements on stability and/or limited output power are violated. Thus, the proposed control algorithm achieves better noise reduction performance than the traditional leaky FxLMS algorithm, which unnecessarily suppresses the control filter at all the frequencies. Simulations and experiments are carried out in a duct ANC system to verify the effectiveness of the proposed algorithm for both the feedforward and feedback ANC systems.

Directional Suppression of Monotone Noises with A Parametric Array Loudspeaker

Monotone noises at high decibels have been identified as a main cause of degradation in people’s mental health. This paper proposes a directional monotone noise reduction method to suppress spatially localized single-frequency noises. The system is designed based on a feedforward active noise control (ANC) structure by implementing filtered-x least mean square (FxLMS) algorithms. Compared with traditional ANC methods, our system employs a parametric array loudspeaker (PAL) as the active noise-canceling source with high audio directivity for directional noise suppression. The system monitors the ambient monotone noise and implements the ANC algorithm in real-time through a software-based platform operating on a generic personal computer (PC). Experimental measurements demonstrate an 8dB reduction of different monotone noises at a 260cm distance from the active source. Compared with traditional ANC methods with a voice coil loudspeaker (VCL) as the noise-canceling source, our PAL-based system achieves similar noise suppression performance with a 5.8 times improvement in the source-to-target distance and 64% reduction in the −3dB audio main lobe beam width. The results prove the advantage of introducing PALs as active-noise-canceling sources for monotone noise suppression with a cost-effective enhancement in operating distances and noise control directivities.

Deep learning-based active noise control on construction sites

Although construction noise pollution has always been a severe issue for governments in metropolitan cities, there is no effective and practical solution to control it. Due to the high nonlinear and transient nature of machinery noises on construction sites, traditional active noise control (ANC) algorithms show a marginal ability to mitigate them. In this paper, a novel high-performance deep-learning-based feedforward ANC controller is proposed to attenuate construction-related noise by considering the delay and nonlinear behavior of acoustic devices. The developed network, with around 128,500 parameters, can be expanded to a multi-channel ANC method without increasing computational costs, and it is suitable for ANC in open space environments like construction sites. Broadband noise attenuation of around 8.3 dB was achieved of a wide variety of construction noises with minor degradation at very high-frequency ranges (7.5–8 kHz). The presented network outperformed traditional and state-of-the-art ANC algorithms.

Delayless partial subband update algorithm for feed-forward active road noise control system in pure electric vehicles

Road noise is one of the dominant noise sources in pure electric vehicles. Active control for road noise is an attractive solution since this technique is suitable for controlling low-frequency noise. Feed-forward active road noise control (ARNC) systems utilize lots of reference signals and corresponding adaptive filters, and the control performance usually improves as the number of reference signals increases. To reduce the computational cost of ARNC systems so that more reference signals can be processed, we introduce the delayless subband structure into ARNC system and a delayless partial update subband with weighted reference signal normalized filtered-x least mean square (DPUS-WRS-NFxLMS) algorithm is proposed in this paper. Based on the traditional delayless subband algorithm, a partial subband update strategy is proposed to reduce the computational cost. Furthermore, the weighted reference signal is introduced for each subband filter. In this way, a modified vector is designed to assign different weights to different reference signal samples so that the convergence performance can be improved and the round-off error can be reduced. In addition, an adjustment strategy for the step size and reference signal weights is designed to make the algorithm have a better balance between the convergence rate and steady-state behavior. Finally, a purely time-delayed secondary path is constructed as the estimated secondary path to avoid the negative impact of the magnitude-frequency characteristics of the actual secondary path. The simulation results prove that the proposed algorithm achieves better control results than the traditional algorithms with lower computational complexity.

A study on hybrid active noise control system combined with remote microphone technique

This paper proposed a hybrid active noise control (HANC) system combined with virtual sensing technique. The Remote Microphone Technique (RMT) method was established in the time domain, and the optimal array of observation sensors of RMT method was determined by Genetic Algorithm (GA). Then with the pre-defined observation filter, a multichannel simplified HANC system combined RMT (msHANC-RMT) method was proposed. The off-line simulations were executed with the data collected from the tests in a semi-anechoic chamber. The results showed that the msHANC-RMT system had the similar control capability compared to the msHANC system in all noise conditions, which can further compress the peak frequency components in the noise spectrum that cannot be detected and controlled by the traditional feedforward ANC (FFANC) system. However, the msHANC-RMT system was more sensitive to delays compared to the FFANC system, once the additional delays exceeded several milliseconds, the feedback structure in msHANC-RMT system lost most of the control capacity.

Implementations of wireless active noise control in the headrest

Working from home went from a temporary result of the pandemic to a way of life. However, peace and quiet are hard to come by. To get rid of distraction, Active Noise Control (ANC) particularly the ANC headphones are widely used to attenuate the undesired noise in daily life. While it works, the prolonged usage of headphone can cause some discomfort. This work describes a wireless ANC system implementation designed for the headrest to reduce the noise distraction while doing away with discomfort caused by prolonged usage of headphone. Wireless microphones are utilized to pick up the noise with a high reference-to-interference ratio, which helps in improving the noise reduction performance of the ANC headrest. This paper investigates the feedforward, feedback, and hybrid ANC structures' noise reduction performances in the ANC headrest. Comparative experimental results shown in this paper indicate the effectiveness of the proposed approach in reducing noise around the headrest.

Experimental tests of a multichannel active noise control system with single and multiple reference signals applied to the cabin of a tractor

A feedforward active noise control system represents a valid solution whenever it is necessary to attenuate a disturbing noise at low frequency. One example of application is the case of tractors, in which the agricultural operators are exposed for several hours per day to loud noise at low frequency, mainly generated by the engine. Generally, the feedforward systems make use of one reference sensor to measure the noise produced by the main source. However, this way of proceeding could be inadequate to describe the disturbing noise, especially when the noise is divided both in structure-borne and air-borne components. In this article, a comparison between the use of a single and multiple reference signals, processed in a multichannel active noise control system applied to the cabin of a motionless tractor, is proposed. In particular, an accelerometer positioned on the turbocharger is used to sense the vibration generated by the engine, while a microphone placed near the engine is used to measure the air-borne noise. The active system implements the filtered-X least mean squares (FXLMS) algorithm to produce the anti-noise signals. The results show that the use of two simultaneously acquired reference signals improves the performance of the active system.

A robust feedforward hybrid active noise control system with online secondary‐path modelling

In this study, a robust feedforward hybrid active noise control (ANC) system with online secondary-path modelling (SPM) is proposed that is capable of not only effectively suppressing the broadband and narrowband noise components but also tracking the secondary path (SP) variations. An finite impulse response online SPM subsystem as well as an efficient decoupling filter are included in the proposed feedforward hybrid ANC (HANC) system. The decoupling filter is a parallel-form bandpass filter bank that consists of multiple bandpass filters that are derived from the second-order infinite impulse response notch filters. It takes the residual noise as its input and separates the broadband component from the narrowband component, with the former used as not only a desired signal for the SPM but also as an error signal for updating the broadband sub-controller, whereas the latter adapted simultaneously to scale the auxiliary white Gaussian noise and to update the narrowband sub-controller. Extensive simulations are conducted with both the synthetic and real SPs as well as the synthetic and real noise signals that are generated by a large-scale factory cutting machine (strand-cutter) to demonstrate the advantages and effectiveness of the proposed feedforward HANC system. Comparisons are also demonstrated with the original HANC system as well as its directly extended version with an online SPM subsystem.

Head-Mounted Multi-Channel Feedforward Active Noise Control System for Reducing Noise Arriving From Various Directions

A head-mounted active noise control (ANC) system based on the single-channel ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1\times 1 \times 1$ </tex-math></inline-formula> ) feedforward control has been studied as a noise reduction method in complicated noise environments such as factories in which various machines are located that generate unwanted noises. However, it is difficult to reduce the noise arriving from various directions because the causality constraint cannot be satisfied. To solve this problem, we developed a head-mounted ANC system based on the multi-channel ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times 1 \times 1$ </tex-math></inline-formula> ) feedforward control. This ANC system has two reference microphones that satisfy the causality constraint. Therefore, the proposed head-mounted ANC system achieves the expansion of noise reducible range of 0-100° compared to that of the conventional head-mounted ANC with the range of 0-60°. In this paper, we examine the effectiveness of the newly developed head-mounted ANC system. In the experiments, we evaluate the effectiveness of placing two reference microphones on noise reduction performance in the case of various arrival direction of the unwanted noise. Experimental results demonstrate that the proposed system increases the noise reducible range and improves the noise reduction performance for two noise sources. In addition, we theoretically prove the effectiveness of the proposed system.