Hybrid Active Noise Control Research Articles

A novel feedforward narrow-broadband hybrid active noise control system for excavator interior noise control

Excavator interior noise is a mixture of engine noise and impulsive noise produced by working device. Hybrid narrow-broadband active noise control (HANC) systems can efficiently eliminate the traditional mixed broad-narrowband noise. However, these HANC systems have drawbacks such as high computational complexity, unable to cope with impulsive noise and inability to obtain the best performance due to parameter selection method. To solve these problems, a novel feedforward narrow broadband HANC system consisting of four subsystems, namely, sinusoidal noise canceller (SNC) subsystem, robust broadband active noise control (RBANC) subsystem, delay narrowband active noise control (DNANC) subsystem, and supporting error calculating subsystem, is proposed. Combining the advantages of delayed least mean square algorithm in DNANC subsystem and Versoria criterion-based filtered-x least mean square algorithm in RBANC subsystem, both the computational efficiency and the robustness when encountering impulsive noise of the proposed HANC system are efficiently improved. In addition, the performance of the proposed HANC system is further improved by changing the key parameters selection method form trial-and-error method to improved particle swarm optimization (IPSO) algorithm with active factor. Both the superiority of the proposed HANC system over existing counterparts and the advantage of the IPSO algorithm with active factor in determining the key parameters are demonstrated by extensive simulations. Real-time HANC experiments in semi-anechoic chamber based on measured excavator interior mixed noise are conducted in this article. Experimental results illustrate that the proposed HANC system achieves good noise elimination performance and also being robust when encountering impulsive noise.

Application of an improved wide–narrow-band hybrid ANC algorithm in a large commercial vehicle cabine

In recent years, active noise reduction technology has become a research hotspot. However, most active noise reduction technologies are developed based on passenger vehicles and are not implemented in large commercial vehicles. The large commercial vehicle sound field space is large, the traditional active noise reduction method is difficult to implement. In order to explore this problem, this paper proposes an improved active noise control method for commercial vehicles: (1) based on the traditional notch filter, a notch FxLMS algorithm based on speed smoothing is proposed; (2) on the basis of the traditional wire–narrowband hybrid ANC algorithm, the reference signal weighting technology is introduced into the wide-band subsystem, and the notch FxLMS algorithm based on speed smoothing is used as the narrowband subsystem, so as to propose an improved wire-narrowband hybrid ANC algorithm. With the help of MATLAB, the simulation model of the designed algorithm is established, and the collected commercial vehicle test noise data is used as the reference signal to simulate and verify the proposed algorithm. The results show that the proposed method has certain practicability.

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.

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.

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.

Maximum versoria criterion applied to hybrid active noise control algorithm for the impulsive noise

In the conventional hybrid active noise control (CHANC) algorithm, the filtered-x least mean square (FXLMS) algorithm is used in both feedforward and feedback structures. However, the FXLMS algorithm does not process the reference signal and the error signal before updating the weight vector, which leads to the inadequate robustness of the CHANC algorithm in the impulsive noise environment. To solve this problem, the maximum versoria criterion is incorporated into the HANC (MVC-HANC) algorithm in this paper. Firstly, the MVC-HANC algorithm employs a novel nonlinear function to compress the error signal. Secondly, the proposed algorithm uses the modified sigmoid function to constrain the reference signal. To further improve the noise attenuation performance, the MVC-HANC algorithm uses a novel exponential function to adjust the step-size adaptively. Simulation and experiment results demonstrate that the proposed algorithm has the better attenuation performance than the conventional HANC algorithm.

Spatially selective active noise control systems.

Active noise control (ANC) systems are commonly designed to achieve maximal sound reduction regardless of the incident direction of the sound. When desired sound is present, the state-of-the-art methods add a separate system to reconstruct it. This can result in distortion and latency. In this work, we propose a multi-channel ANC system that only reduces sound from undesired directions, and the system truly preserves the desired sound instead of reproducing it. The proposed algorithm imposes a spatial constraint on the hybrid ANC cost function to achieve spatial selectivity. Based on a six-channel microphone array on a pair of augmented eyeglasses, results show that the system minimized only noise coming from undesired directions. The control performance could be maintained even when the array was heavily perturbed. The proposed algorithm was also compared with the existing methods in the literature. Not only did the proposed system provide better noise reduction, but it also required much less effort. The binaural localization cues did not need to be reconstructed since the system preserved the physical sound wave from the desired source.

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.

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.

Multi-channel wireless hybrid active noise control with fixed-adaptive control selection

Active noise control (ANC) is now a must-have feature in various headphones to attenuate unwanted external noise leaked into the headphones. The conventional ANC headphone typically uses an earcup-mounted reference microphone to pick up the reference signal and send it to the chip’s control filter, which generates anti-noise inside the earcup to destructively interfere with the leaky noise signal. Previously, a novel type of wireless feedforward ANC structure was devised to achieve greater noise reduction by acquiring a higher reference-to-interference ratio. To further reduce computational complexity and relax causality constraints over traditional ANC algorithms, a modification to this structure is proposed that employs a hybrid feedforward–feedback structure in conjunction with a fixed-adaptive control selection (FAS). Furthermore, numerical simulations and real-time experiments are performed in this paper to validate the effectiveness of the wireless hybrid ANC with the FAS technique.

Self-balancing collaboration between linear and nonlinear adaptive sub-filters for hybrid active noise control

Conventional adaptive filters for active noise control (ANC) are troubled by the trade-off between convergence speed and steady state error, especially when nonlinearity plays an important role in system model. In this paper, a hybrid ANC algorithm called FBFLANN is constructed by the collaboration of FIR and bilinear functional link artificial neural network. The characteristics of linear and nonlinear sub-filters are analyzed and utilized to facilitate the adaptability in noise reduction. A convex factor is employed to automatically balance the contribution of two sub-filters, achieving faster convergence and higher accuracy in the presence of nonlinear distortions. The mathematical working and updating rules of the controller are derived to regulate the ANC process theoretically. The effectiveness of the proposed FBFLANN algorithm is demonstrated by numerous simulation studies considering diverse nonlinear acoustic path models as well as acoustic feedback interference. Hardware ANC platform is built up to verify the real-time noise control performance in physical noisy environments. The simulation and experiment results confirm the applicability and prospects for further development of the presented architecture in noise control scenarios.

An active noise control system based on reference signal decomposition

The performance of the traditional active noise control system will degrade severely when the target noise has both broadband and narrowband components. At present, many scientists have discussed this topic, but the problems that certain known conditions are required or high computational complexity still exist. In This article, we propose a reference signal decomposition normalized filtered-x least mean square (RSD-NFxLMS) algorithm. By means of linear prediction (LP), the narrowband signal will be separated from the reference signal, then the broadband and narrowband signal are processed by two parallel systems respectively. Besides, we proposed a coefficients-weighting (CW) method to balance the contradiction between convergence speed and steady-state error, which significantly improves the performance of the algorithm. The simulation results show that the algorithm can achieve the same effect as Hybrid ANC (HANC) system without using known conditions, especially in low signal-to-noise ratio (SNR) and low frequency conditions.

A hybrid multi-reference subband control strategy for active noise control headphones

Multi-reference feedforward Active Noise Control (ANC) has been shown to provide increased noise mitigation capability in ANC headphones compared to a single reference feedforward controllers, due to the availability of additional time advanced information. Recent studies have also shown that the integration of a single-reference feedforward controller and a feedback controller increases both the noise cancellation bandwidth and system stability, therefore, a corresponding hybrid version of the multi-reference control strategy has been developed and is presented in this paper. The hybrid multi-reference ANC (HMRANC) system is comprised of a multi-reference feedforward control unit acting in conjunction with a feedback ANC system. In addition, to overcome the high computational demand of the hybrid structure, a delayless subband version of the HMRANC system is also presented in this paper. The proposed HMRANC and delayless subband HMRANC headphone systems achieve an improvement of 5–10 dB over the previously proposed hybrid ANC headphone system for different acoustic field scenarios. Moreover, the delayless subband HMRANC headphone system is 40% less computationally demanding then HMRANC and 10% less demanding than HANC headphone systems.

A new feedforward and feedback hybrid active noise control system for excavator interior noise

Excavator interior noise is composed of the engine order narrowband noise and the impulsive broadband noise caused by working device. In situations where only narrowband reference signal can be obtained, the feedforward active noise control (ANC) system can just eliminate the narrowband component, failing to control the broadband noise. Hybrid feedforward and feedback ANC (HANC) systems are useful for such applications where the reference signals can be partially obtained. However, existing HANC systems have the following drawbacks: coupling between subsystems; inaccurate error and reference signals; high computational complexity; performance degradation in response to the impulsive noise. To solve the above problems, this paper proposes a new feedforward and feedback HANC system consisting of 3 subsystems, namely, a delayed feedforward narrowband subsystem, a robust feedback broadband subsystem, and a supporting error calculating (SEC) subsystem. In the proposed HANC system, not only subsystems are decoupled, but also accurate error and reference signals are provided by SEC subsystem. In addition, calculating efficiency is improved by applying the delayed notch least mean square (DLMS) algorithm to the feedforward subsystem, and the system robustness is promoted by adopting the robust algorithm into the feedback subsystem. Numerous computer simulations are performed on the excavator interior noise measured under actual operating conditions. The corresponding results demonstrate the superior performance of the proposed HANC system in terms of the power spectral density of residual error, average noise reduction, robustness of the system, and calculation efficiency to the existing HANC systems. Real-time experiments on excavator interior noise showed that the proposed HANC system was efficient in eliminating broadband and narrowband mixture noise in practice.

Hybrid active and passive noise control in ventilation duct with internally placed microphones module

A feedforward active noise control (ANC) system combined with the passive silencer is built to reduce the acoustic noise propagating through the ventilation duct. The passive silencer consists of two layers which are made of aluminum plate and the perforated panels respectively, the cavity between the two layers is filled with the melamine foam. To overcome the two issues encountered in the active noise control for ventilation duct, i.e., the turbulent flow noise and the acoustic feedback, the emphasis of ANC system is the internally placed microphones module. The module is made of a perforated panel shell filled with the melamine foam, the reference and error microphones are both placed in the melamine foam. The real experiments show that the passive silencer has more than 20 dB noise attenuation at frequencies above 600 Hz, ANC can obtain more than 10 dB noise attenuation from 70 Hz to 200 Hz (the maximum 17 dB at 150 Hz) when the wind speed increases from 5 m/s to 10 m/s. In addition, the module is easy to install and maintain, and its manufacturing cost is also acceptable.

A novel adaptive step-size hybrid active noise control system

The conventional hybrid active noise control (HANC) system adopts the standard filtered-x least mean square (FxLMS) algorithm to adapt its control filters. However, the constant step size in the algorithm leads to not only the contradiction between convergence rate and steady-state noise reduction, but inadequate robustness under certain noise circumstances. For performance improvement, a new adaptive step-size method is incorporated into the HANC (ASHANC) system to optimize the adaptation of the filters. It combines the strengths of the variable step-size FxLMS (VSFxLMS) algorithm and the modified normalized FxLMS (MNFxLMS) algorithm. Different step-size adjustment strategies can be obtained by setting specific parameters. Furthermore, to obtain the best performance of the system, we develop a method to determine the involved key parameters on the basis of the improved particle swarm optimization (IPSO) algorithm. The objective function of the IPSO algorithm takes the convergence rate and noise reduction into consideration to search for optimum values. Simulation results demonstrate that the proposed ASHANC system achieves faster convergence rate, better noise reduction, and enhanced robustness than the other investigated systems.

A modified feedforward hybrid active noise control system for vehicle

The feedforward hybrid active noise control (HANC) system combines the strengths of the narrowband ANC (NANC) system and the broadband ANC (BANC) system. Taking this advantage into account, this paper applies it to attenuate the vehicle interior noise mixed with narrowband and broadband components. However, in the HANC system, the NANC subsystem and BANC subsystem are fed a common error signal which depends on the combined secondary signals from the both subsystems. This causes the problem of mutual coupling and hence affects the noise reduction performance. To tackle the problem, we propose a modified HANC (MHANC) system in this paper. In the MHANC system, the error signal of each ANC subsystem is independently synthesized on the basis of the estimated primary and secondary signals. Note that the NANC system for engine order noise control suffers performance deterioration when the fluctuating real-time engine speed signal is used for constructing internal reference signals. For performance improvement, an enhanced NANC (ENANC) system is developed by smoothing the fluctuating engine speed signal. Meanwhile,the ENANC system is incorporated in the MHANC system to form an enhanced MHANC (EMHANC) system. Simulations were performed on the vehicle interior noise recorded under actual driving conditions. The corresponding results demonstrate the superiority of the proposed MHANC and EMHANC systems.

A Hybrid Active Noise Control System for the Attenuation of Road Noise Inside a Vehicle Cabin.

This paper proposed a local active control method for the reduction of road noise inside a vehicle cabin. A multichannel simplified hybrid active noise control (sHANC) system was first developed and applied to the rear left seat of a large sport utility vehicle (SUV). The attenuation capability of the sHANC system was investigated through simulations, using reference signals provided by accelerometers on the suspensions and bodywork of the vehicle and microphones on the floor of cabin, respectively. It was shown that compared to the traditional feedforward system, the sHANC system using either vibrational or acoustical reference signals can produce a significant suppression of the narrowband peak noise between 75 and 80 Hz, but the system lost the control capability in a range of 100–500 Hz when the acoustic signals were used as references. To reduce the practical implementation costs while maintaining excellent reduction performance, a modified simplified hybrid ANC (msHANC) system was further proposed, in which combined vibrational and acoustical signals were used as reference signals. The off-line analyses showed that four reference accelerometers can be substituted by ten microphones without compromising attenuation performance, with 3.7 dBA overall noise reduction being achieved. The effect of delays on the reduction performance of msHANC system was also investigated. The result showed that the msHANC system was more sensitive to the delays compared to the sHANC system if using only vibrational reference signals.

Alternative switching hybrid ANC

The feedforward active noise control (FF ANC) technique has been widely used to cancel the broadband noise in many practical applications. However, it fails to cope with the uncorrelated narrow-band disturbance picked up by the error sensor, which is independent of the reference signal picked up by the reference sensor. Hence, the alternative switching hybrid ANC has been proposed in the paper to attenuate this kind of uncorrelated narrow-band disturbance effectively. Furthermore, compared with the conventional hybrid ANC algorithms, the proposed algorithm alternatively switches to do updating between the feedforward (FF) and feedback (FB) ANC. The algorithm, thus, saves the computations and achieves a faster convergence speed. The numerical simulations and real-time experiments in the paper validate the effectiveness of the proposed algorithm, which exhibits better convergence and noise reduction performance than other hybrid active control algorithms.