Adaptive variable step-size neural controller for nonlinear feedback active noise control systems

Adaptive filter techniques and the filtered-x least mean square (FxLMS) algorithm have been used in Active Noise Control (ANC) systems. However, their effectiveness may degrade due to the nonlinearities and modeling errors in the system. In this paper, a new feedback ANC system with an adaptive neural controller and variable step-size learning parameters (VSSP) is proposed to improve the performance. A nonlinear adaptive controller with the FxLMS algorithm is first designed to replace the traditional adaptive FIR filter; then, a variable step-size learning method is developed for online updating the controller parameters. The proposed control is implemented without any offline learning phase, while faster convergence and better noise elimination can be achieved. The main contribution is that we show how to analyze the stability of the proposed closed-loop ANC systems, and prove the convergence of the presented adaptations. Moreover, the computational complexities of different methods are compared. Comparative simulation results demonstrate the validity of the proposed methods for attenuating different noise sources transferred via nonlinear paths, and show the improved performance over classical methods.     

A novel feedback active noise control for broadband chaotic noise and random noise

The feedback active noise control (ANC) can be seen as a predictor, the conventional method based on filtered-x least mean square (FXLMS) algorithm can only be useful for linear and tonal noise, but for nonlinear and broadband noise, it is useless. The feedback ANC using functional link artificial neural networks (FLANN) based on filtered-s least mean square (FSLMS) algorithm can reduce some nonlinear noise such as chaotic noise, but the noise cancellation performance is not very well, at the same time, it is not useful to random noise. To solve the problem above, a new feedback ANC using wavelet packet FXLMS (WPFXLMS) algorithm is proposed in this paper. By decomposing the broadband noise into several band-limited parts which are predictable and each part is controlled independently, the proposed algorithm can not only suppress the chaotic noise, but also mitigate the random noise. Compared with FXLMS and FSLMS algorithms, proposed WPFXLMS algorithm also holds the best performance on noise cancellation. Numerous simulations are conducted to demonstrate the effectiveness of the proposed WPFXLMS algorithm.     

Time–frequency-domain filtered-x LMS algorithm for active noise control

This paper presents a time–frequency-domain filtered-x LMS (FXLMS) algorithm for active noise control (ANC) based on the short-time Fourier transform (STFT). We show that proposed algorithm has much reduced computational complexity and better convergence performance, as compared with the time-domain FXLMS algorithm. Additionally, computer simulations show that a time–frequency-domain FXLMS algorithm for ANC is effective in canceling non-stationary noise while a frequency-domain FXLMS algorithm remains inadequate at this task.     

Design and experimental tests of active control barriers for low-frequency stationary noise reduction in urban outdoor environment

Active noise control (ANC) techniques are based on the emission of an antiphase signal in order to cancel the noise produced by a primary source. ANC has been successfully applied especially for reducing noise in confined environments, such as headphones and ducts. In this study, we present an application of ANC concepts to the design of an anti-noise barrier for an outdoor environment and its experimental testing. Even though passive techniques are effective in noise reduction at middle-high frequencies, they become less efficient at low frequencies (below 300 Hz) due to the limited dimensions of commonly deployable barriers. In this paper, we analyze the properties of a low-cost active noise system able to efficiently operate on stationary, almost pure-tone, low-frequency noise, such as that produced by electrical transformers and reactors in power and transformation plants. A prototype has been implemented and on-the-field experimental tests have been carried out. The results (confirmed also by numerical simulations) demonstrate a remarkable efficiency in the far field, with a reduction up to 15 dB with respect to the absence of the ANC system.     

Convex combination of nonlinear adaptive filters for active noise control

This paper proposes a nonlinear active noise control (ANC) system based on convex combination of a functional link artificial neural network (FLANN) and a Volterra filter. Simulation study reveals enhanced noise cancelation performance of the proposed ANC system over the ones based on its component filters.     

多通道FxAP算法的电动汽车路噪控制

汽车噪声控制是主动噪声控制领域中经典的问题.伴随着电动化的普及,路噪控制将取代内燃机噪声控制,逐渐成为汽车噪声控制的主要领域.针对传统车内路噪控制系统适应性差、算法收敛速度慢、降噪量不足的问题,该文使用了多通道滤波-x仿射投影(FxAP)算法加快收敛速度,从而实现对噪声的快速追踪并控制.通过搭建了车内多通道头靠噪声控制...     

Improving performance of FxRLS algorithm for active noise control of impulsive noise

Active noise control (ANC) systems employing adaptive filters suffer from stability issues in the presence of impulsive noise. New impulsive noise control algorithms based on filtered-x recursive least square (FxRLS) algorithm are presented. The FxRLS algorithm gives better convergence than the filtered-x least mean square (FxLMS) algorithm and its variants but lacks robustness in the presence of high impulsive noise. In order to improve the robustness of FxRLS algorithm for ANC of impulsive noise, two modifications are suggested. First proposed modification clips the reference and error signals while, the second modification incorporates energy of the error signal in the gain of FxRLS (MGFxRLS) algorithm. The results demonstrate improved stability and robustness of proposed modifications in the FxRLS algorithm. However, another limitation associated with the FxRLS algorithm is its computationally complex nature. In order to reduce the computational load, a hybrid algorithm based on proposed MGFxRLS and normalized step size FxLMS (NSS-FXLMS) is also developed in this paper. The proposed hybrid algorithm combines the stability of NSS-FxLMS algorithm with the fast convergence speed of the proposed MGFxRLS algorithm. The results of the proposed hybrid algorithm prove that its convergence speed is faster than that of NSS-FxLMS algorithm with computational complexity lesser than that of FxRLS algorithm.     

Enhancement of noise reduction efficiency based on compensation in the ANC headset using fixed-point DSP

In this paper, we have proposed a new algorithm considering commutation error and feedback effect to enhance the convergence rate and noise reduction efficiency of ANC controller. In order to improve noise reduction performance of the ANC headset with fixed-point DSP, we have proposed a new FxLMS algorithm, FxLMS CF, which considers the commutation error and feedback. Also, using a non-real-time simulation, we have decided the phase and amplitude compensation factors of anti-noise signal considering round-off and quantization error, nonlinear distortion and delay of analog device. We estimated the phase and amplitude compensation factors by simulation without using any special measuring devices or analysis devices, and reduced the broadband noise by 24 dB.     

Adaptive Laguerre filters for active noise control

Feedforward controllers are used in many active noise control (ANC) systems to generate destructive interference in noise fields. An ideal feedforward ANC controller should have an infinite impulse response (IIR) transfer function, but most available feedforward ANC controllers have finite impulse responses (FIR) instead. The main reason is related to the adaptation algorithms of ANC systems. In general, adaptive FIR filters converge faster with guaranteed stability. In this study, the adaptive Laguerre filter is proposed and tested in an ANC application with positive experimental effects. The new ANC controller is an IIR filter, but its adaptation is similar to that of a FIR filter with fast convergence and guaranteed stability. Detailed explanations and analysis are presented in the main text.     

基于脉冲声分离的刚性球散射声控制

提出了一种基于脉冲声的三维空间中刚性球散射声分离方法,并利用前馈、固定系数控制方式对分离出的散射声进行有源控制,抑制散射声强度,实现了刚性球散射体在观测点处“声学不可见”。该方法利用脉冲信号作为初级噪声,通过有无刚性球时传声器采集脉冲信号的差值确定散射声大小,实现散射声与声源直达声的分离。对分离出的散射声进行多通道有源控制以验证该文所提分离方法及控制系统的有效性。实验结果表明,700~1000 Hz范围内,有源控制开启后,双通道散射声的平均降噪量大于5 dB,多通道散射声的平均降噪量大于8 dB,且误差传声器处采集的残余声场与无刚性球时采集的初级声场信号波形基本一致,实现了刚性球散射体在误差传声器处“声学不可见”。此外,参考传声器布放位置的选取问题也在该文做了详细讨论。     

Binaural active noise control using parametric array loudspeakers

This paper reports the binaural active noise control (ANC) system developed to deal with factory noise. The control points are located in the vicinity of the left and right ears of a worker sitting along the production line. Due to the complicated safety requirements in the factory, secondary sources and error microphones are not allowed to be placed near the worker. Therefore, the proposed ANC system employs the feedforward structure and adopts the parametric array loudspeakers (PALs) as the secondary sources. The PAL is a type of directional loudspeaker that generates a much narrower sound field as compared to the conventional loudspeaker. Once the proposed ANC system has been trained offline, the error microphones can be removed. The performance of the binaural ANC system is successfully demonstrated based on a digital signal processor (DSP) implementation.     

Comparison of convergence characteristics of adaptive IIR and FIR filters for active noise control in a duct

There are perceived drawbacks to using adaptive IIR filters, as opposed to adaptive FIR filters, for active noise control (ANC). These include stability issues, the possible convergence of estimated parameters to biased and/or local minimum solutions and relatively slow rate of convergence. Stability issues can generally be resolved easily using well-established methods. In this Technical Note convergence rates are compared with particular reference to the active control of noise in a duct, for which the dynamics of the cancellation path are important. The characteristics of this application of ANC set it apart from usual signal processing applications of adaptive IIR filters and this has implications for the convergence properties. Various control approaches are considered: IIR least mean squares (IIR-LMS), IIR recursive least squares (IIR-RLS) with FASPIS (Fast Algorithm Secondary Path Integration Scheme) and FIR-LMS. Numerical examples are presented. It is seen that the cancellation path dynamics generally have the effect of changing the performance surface of the estimated IIR filter from bimodal to unimodal, which has consequences for improving the convergence rate of adaptive IIR filters. It is also seen that IIR-RLS has a comparable rate of convergence to FIR-LMS, with the steady-state performance being as good or better.     

Active control of intermittent noise in a room

I.IntroductionThereverberantnoisesmaybereducedwithanactivenoisecontrol(ANC)systcmformedbyacornermicrophonc-amplifier-1oudspcakersystemina.oom.lllThismeth-odbascdonthenormalmodccancelingprincip1chasalreadybeenclarifiedbothinthco-ryandexperimcnts,andthclimitationandpotcntialityofitsapp1icationalsodiscussedinapreviouspaper.Thediscussionsinthepastlimitedmost1ytothesteadyconditionofnoiscfield,andthisisextendedtothetransientcondihoninthcprcsentwork,viz.thein-llucnceofthecornerANCsystemwhenthenois…     

Simulations and experiments for hybrid noise control systems

The purpose of this study is to explore the effects of sound elimination in a cylindrical duct by combining a reactive muffler and active noise control (ANC) system. Besides the exploration via experiment of the combined noise control system, a Grey prediction based on Grey theory is also applied to ANC for this hybrid system.In the experiment for this system, a combined adaptive algorithm is adopted. The results of sound elimination are compared between cases with ANC systems installed before the muffler and after the muffler. The results indicate that the sequence of arrangement of muffler can influence the results of active noise control. According to the results of experiment and simulation, the effect of noise reduction in ANC system is influenced extremely by reference signal received. The transmission loss and insertion loss in this system are also discussed in details. Besides, the experimental results indicate that the hybrid system has the advantages over a traditional muffler when the muffler is not designed for the frequency of the noise. Furthermore, the mathematic simulation for acoustic field in a cylindrical duct with a muffler is performed in order to verify the experiment results. Finally, Grey theory is applied to estimate the expected signals in order to perform a computer simulation of Grey prediction to explore effects of the ANC system. The results indicate that application of Grey theory gives a good control for the hybrid system.     

A robust filtered-s LMS algorithm for nonlinear active noise control

The performance of a nonlinear active noise control (ANC) system based on the recently developed filtered-s least mean square (FsLMS) algorithm deteriorates when strong disturbances in the ANC system are acquired by the microphones. To surmount this shortcoming, a novel robust FsLMS (RFsLMS) algorithm is proposed for a functional link artificial neural network (FLANN) based ANC system. The new ANC system is least sensitive to such disturbances and does not call for any prior information on the noise characteristics. The results obtained from simulation study establish the effectiveness of this new ANC scheme.     

Active noise control in a duct by an analog neural network circuit

Conventional active noise control (ANC) in ducts has been realized with digital signal processing. The physical size of the conventional ANC systems is usually large owing to the signal processing interval, and the cost of the system depends on the price of the digital signal processor (DSP). This paper proposes a new ANC system with an analog neural network circuit, which will process signals in short time periods without DSP. The proposed neural network circuit has a simple structure consisting of analog multipliers and an integrator, and we simulated the performance of the circuit by HSPICE. We also fabricated a circuit connected to a real duct and confirmed operation of the proposed ANC system.     

Implementation of active noise control in a multi-modal spray dryer exhaust stack

Tonal noise emitted from large-diameter spray dryer exhaust stacks used in the dairy industry can give rise to complaints from nearby communities. In many cases, the tone at the fan blade passing frequency is characterized by a frequency above the first mode cut on frequency of the exhaust stack and both its amplitude and the frequency are time varying. The variation in amplitude is a result of turbulence and temperature variations in the duct which cause angular variations in the nodal plane of modes with diametrical nodes. This in turn results in large fluctuations in sound pressure with time at any specified location in the duct, thus presenting a significant challenge for an ANC system with fixed control source and error sensor locations. In many food processing industries, the use of sound absorptive materials in silencers is not acceptable and, particularly when the fan speed is variable, it is difficult to achieve an acceptable passive solution at a reasonable cost. Here, the design and implementation of an active noise control system for tonal noise propagating above the cut-on frequency of the first higher order mode in large size cylindrical industrial exhaust stack is discussed, where the frequency and amplitude vary significantly and relatively rapidly with time. Physical system design principles and control algorithm optimization for a practical active noise control system are presented. Finally, real time control results which were achieved by a prototype installation on a large-diameter, in-service exhaust stack are given. Significant noise reductions were achieved in the community.     

远程干涉型光纤传感系统的非线性相位噪声分析

以远程干涉型光纤传感系统为背景, 研究了系统非线性相位噪声构成, 对各构成要素的具体影响进行了详细分析和综合评价, 简要讨论了噪声抑制方案. 研究表明, 系统相位噪声主要包括强度噪声转化而来的相位噪声、非线性效应引起激光 线宽展宽导致的相位噪声以及自相位调制和交叉相位调制引入的相位噪声. 受激布里渊散射和四波混频可引入强度噪声并转化为相位噪声, 对于探测带宽较窄的光纤传感系统, 四波混频引入的该部分噪声往往可以忽略. 受激布里渊散射、四波混频和调制不稳定性都可引起激光线宽展宽从而造成相位噪声的增大. 当系统信道数目较多时, 交叉相位调制对相位噪声的贡献不可忽略. 所得结论对远程干涉型光纤传感系统的实际应用具有重要的指导意义.     

有源噪声控制的一种变换域算法

有源噪声控制广泛应用于中低频噪声控制中。传统的有源控制都是在时域内使用LMS算法进行控制，由于LMS算法的收敛速度跟输入信号的自相关矩阵特征值分布有关，当特征值分布较大时，LMS算法的收敛速度会变的很慢。本文使用离散余弦变换(DCT)技术，在变换域内进行有源噪声控制的研究，同时考虑了变换域约束。仿真表明算法的有效性。     

双模环型激光增益噪声模型的非线性效应

讨论了一个双模环型激光增益噪声模型，其中考虑了完全饱和效应且乘法噪声由增益系数涨落引起。在共振及两模具有相同泵参数时，获得了光强联合定态分布的精确解析表达式。通过与现有的双模激光摸型（其中乘法噪声由损失系数涨落引起）的比较，发现乘法噪声系数的非线性效应减弱了乘法噪声给激光光强统计性质带来的反常特性，并且这种减弱随着乘法噪声增强或损失系数减小而愈加明显。