A nonlinear active noise control algorithm for virtual microphones controlling chaotic noise

In active noise control (ANC) systems, virtual microphones provide a means of projecting the zone of quiet away from the physical microphone to a remote location. To date, linear ANC algorithms, such as the filtered-x least mean square (FXLMS) algorithm, have been used with virtual sensing techniques. In this paper, a nonlinear ANC algorithm is developed for a virtual microphone by integrating the remote microphone technique with the filtered-s least mean square (FSLMS) algorithm. The proposed algorithm is evaluated experimentally in the cancellation of chaotic noise in a one-dimensional duct. The secondary paths evaluated experimentally exhibit non-minimum phase response and hence poor performance is obtained with the conventional FXLMS algorithm compared to the proposed FSLMS based algorithm. This is because the latter is capable of predicting the chaotic signal found in many physical processes responsible for noise. In addition, the proposed algorithm is shown to outperform the FXLMS based remote microphone technique under the causality constraint (when the propagation delay of the secondary path is greater than the primary path). A number of experimental results are presented in this paper to compare the performance of the FSLMS algorithm based virtual ANC algorithm with the FXLMS based virtual ANC 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.     

Active control of transformer noise with an internally synthesized reference signal

A method of using an internally synthesized signal of preset frequencies as the reference signal for transformer noise control is proposed in this paper. The feasibility of applying the method in a specific transformer algorithm is investigated, where the effects of frequency mismatch and secondary path delay on the steady-state behavior of the transformer algorithm are analyzed and compared with the filtered-x least mean square algorithm. It is found that the noise reduction performance degrades with the increase of secondary path delay and frequency mismatch, but can be improved by using a larger convergence step size and a faster update rate. With parameter studies, the feasibility of applying the transformer algorithm with an internally synthesized reference signal to practical transformer noise control is verified by both numerical simulations and experiments.     

存在声反馈的前馈有源噪声控制系统性能分析

在一些应用场合,前馈有源噪声控制系统中次级源产生的声信号会反馈至参考传声器,影响参考信号质量和系统稳定,导致控制性能下降。引入了等效次级路径的概念,并通过等效次级路径与实际路径的相位偏差分析存在声反馈时的收敛性能。若某些频率的相位偏差大于90°,则这些频率附近将较难收敛,降噪性能下降,甚至导致系统不稳定。通过仿真和实验对单指向传声器声学方法、自适应滤波u型最小均方差(FuLMS)算法、反馈中和算法和在线建模算法共4种解决声反馈问题的方法的性能进行了比较。结果表明,4种方法都能提高存在声反馈时的前馈有源噪声控制系统的性能,有效解决声反馈引起的问题,但各有优缺点。单指向传声器方法最为方便,但低频指向性较差。FuLMS算法运算量较低,但不能保证收敛。反馈中和算法性能最好,但当系统时变时鲁棒性较差。在线建模算法不需要额外滤波器,但由于参数调节复杂,降噪性能稍差。      

A simplified adaptive feedback active noise control system

In the adaptive feedback active noise control system based on the internal model control (IMC) structure, the reference signal is regenerated by synthesizing the error signal and the secondary signal filtered with the estimation of the secondary path, hence more computation load and extra programming are required. Motivated by the engineering truth that the primary noise cannot be completely cancelled in most practical active noise control applications and the error signal still contains some portions of the primary noise, a simplified adaptive feedback active noise control system is proposed in this paper, which adopts the error signal directly as the reference signal in an adaptive feedforward control system and utilizes the leaky filtered-x LMS algorithm to update the controller. The convergence properties of the proposed system are investigated and its advantages are discussed by comparing with other feedback control systems as well as the weakness. Finally, simulations and experiments are carried out to demonstrate the effectiveness of the proposed system.     

Development of adaptive algorithm for active sound quality control

This paper develops an active sound-quality control (ASQC) system based on the active noise equalization (ANE) technique, and optimizes it with the filtered-error least mean square (FELMS) algorithm and normalized reference signal generator. The ASQC system controls the sound quality of products such as engines by changing the amplitudes of harmonics. This optimized system uses the FELMS algorithm to limit disturbances in the passband caused by uncorrelated interferences with high gains in the secondary path, thereby increasing the system stability. It achieves fast convergence by normalizing the amplitudes of internally generated sinusoids in the reference signal according to the magnitude response of the secondary path at the corresponding frequencies. Computer simulations demonstrate the desired spectral shaping capability with faster convergence and reduced passband disturbance.     

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.     

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.     

一种能量比调控的有源噪声控制算法*

在前馈有源噪声控制系统中,建模信号与控制信号相互影响,建模信号的引入会导致系统降噪性能变差。为了减小建模信号的影响,提出一种基于能量比调控的次级通道在线建模有源噪声控制算法。利用控制过程与建模过程的误差能量比构造步长调控函数,分别调节控制过程与建模过程的步长值,从而减弱两者的相互影响。在次级通道建模过程中,对建模步长值采取分段调控的方法,并通过建模步长值的变化来调节建模信号,从而提升系统降噪性能。仿真结果表明,对于低频噪声信号的有源噪声控制,相比已有算法,提出的算法能获得较快的建模收敛速度和较高的降噪量。     

多通道窄带Fx-Newton时频算法及动力机械有源隔振实验

提出了一种多通道窄带Fx—Newton算法,用多个控制器并联控制各窄带带通滤波器提取的多根线谱。离线辨识次级通道频响矩阵并求逆后,只需L×L个(通道数为L)2阶滤波器即可实现次级通道逆模型滤波,从而使控制器系数向最优值迅速收敛。还提出了窄带滤波相位差的自适应补偿算法,可提高线谱频率波动时的控制鲁棒性。在200kw实船柴油发电机有源无源隔振装置上进行了实验,结果表明该算法可同时控制10~11根线谱,使每根线谱衰减10~35dB。该算法运算量小,在保证收敛稳定性的同时、收敛速度大于FxLMS算法(尤其在次级通道矩阵特征值分散度大的情况)。      

A waveform synthesis algorithm for active control of transformer noise: implementation

For the active control of the transformer noise, a newly developed adaptive algorithm based on waveform synthesis was proposed in [19], where a comparison of the performance of the proposed algorithm with the FXLMS algorithm made on a single channel system showed the feasibility of the algorithm. This paper describes the implementation of the proposed algorithm on a multiple channel adaptive control system, which is used to control the noise radiated by a small transformer in an anechoic chamber. The implementation shows that the proposed algorithm requires less memory and less computation load than a typical implementation of the FXLMS algorithm and that a controller realised with the proposed algorithm can effectively reduce transformer noise and be quite robust.     

Comodulation masking release as a function of bandwidth and test frequency

Comodulation masking release (CMR) was investigated as a function of signal frequency (0.5-4.0 kHz) and the total bandwidth of noise centered on the signal frequency. Taking noncomodulated noise of the same bandwidth as the reference condition, CMR for modulated noise increased with increasing bandwidth of the flanking noise outside the critical band centered on the signal tone; however, this growth asymptoted for broad total bandwidths. These bandwidth effects were expressed by scaling the width of the flanking bands beyond the critical band centered on the signal frequency, approximately according to a critical bandwidth scale. After this scaling, signal frequency had negligible effect on CMR magnitude. For the low modulation frequencies involved, a beneficial effect on CMR at high carrier frequencies would not be expected, and none was observed. Some further trends in the masked thresholds in comodulated and noncomodulated conditions, and the choice of appropriate reference condition are discussed.     

Control of modulated vibration using an enhanced adaptive filtering algorithm based on model-based approach

Conventional adaptive filtering algorithms, typically limited to the control of single or multiple sinusoids, are not appropriate to control modulated vibrations, especially in the presence of rich side band structures. To overcome this deficiency, a new control algorithm is proposed that introduces a feedback loop with the model predictive sliding mode control (MPSMC) in the adaptive filtering system. Several amplitude and frequency modulation cases are first computationally studied, and conventional and proposed methods are comparatively evaluated in terms of estimation error, performance in time and frequency domains, stability, and uncertainty in the reference signal. To experimentally validate the proposed algorithm, an active strut (with longitudinal vibrations) is constructed. Overall, the proposed adaptive algorithm yields superior reductions at the main frequencies and at side bands; also, good attenuation is found on a broadband basis.     

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.     

High angle phase modulated low coherence interferometry for path length resolved Doppler measurements of multiply scattered light

We describe an improved method for coherence domain path length resolved measurements of multiply scattered photons in turbid media. An electro-optic phase modulator sinusoidally modulates the phase in the reference arm of a low coherence fiber optic Mach-Zehnder interferometer, at a high phase modulation angle. For dynamic turbid media this results in Doppler broadened phase modulation interference peaks at the modulation frequency and its multiples. The signal to noise ratio is increased by almost one order or magnitude for large modulation angles and the shape of the spectral peaks resulting from the interference of Doppler shifted sample waves and reference light is not changed. The path length dependent Doppler broadening is compared with the theoretical predictions in the single scattered and diffusive regimes. The experimentally measured optical path lengths are validated with the Monte Carlo technique.     

一种基于两块PEM调制器的光谱测量方法

弹光调制干涉信号范围为百赫兹到数十吉赫兹之间,而由于探测器阵列无法对该等级频率实现有效响应,因此,该情况使弹光调制器在光谱成像工作中受到限制。为了解决该问题,发展了一种使用两块具有相近谐振频率的PEM,并基于该频率差进行光信号调制的方法。该方法将两个弹光调制器分别工作在数值略有差异的频率f₁和f₂上,被测光通过双弹光调制器实现差频调制,因此干涉信号中产生载有被测光的低频调制分量,低频调制频率是以δ_i(σ,t)=δ_0i(σ)sin(ω_it)为基频的一系列倍频信号,该低频调制信号使用普通探测器即可实现探测,再将直流和高频信号滤波后,仅对调制信号后的低频成分进行对应的运算即可得到被测光谱。由于该频率差比所使用PEM的谐振频率低2至3个数量级,因此,该方法可使探测器获得更多的响应时间,而且由于该方法并不需要所使用的两块PEM具有严格一致的谐振频率和相同的光程差,降低了系统本身的设计难度。     

几种自适应IIR陷波器的复数算法及其应用

在自适应IIR陷波器实数算法的基础上,本文提出了三种基于梯度的自适应IIR陷波器的复数算法,并进行了仿真比较。结果表明,这三种复数算法均可检测复信号,并估计信号频率,其中"改进的"简化格型IIR陷波器复数算法收敛速度快、低信噪比下稳定性能好。湖上试验表明该算法不仅实时性好,而且在低信噪比下的检测效果令人满意。     

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.     

基于L型延迟阵列调制宽带转换器的信号载频和二维到达角联合估计

针对现有的基于欠采样的频率和二维到达角的联合估计存在结构复杂问题,本文提出了一种基于调制宽带转换器技术的L型延迟阵列接收结构.利用延迟通道与未延迟通道采样值之间的相位差可直接估计载频,进而计算二维到达角,无需额外的参数配对操作,避免了配对步骤引入的误差和复杂度的提升.并结合所提L型延迟阵列结构的特点构造相关矩阵和三线性模型,提出了两种参数估计算法,一种基于旋转不变子空间算法,计算量小,适用于需要实时处理的场景;另一种基于正则分解技术,鲁棒性较好,适用于信噪比较低的应用场景.仿真实验表明该方法能较好地从欠奈奎斯特样本中估计目标的载频和二维到达角参数.     

生物组织单光程光谱技术的理论研究

高灵敏度光谱检测技术在临床诊疗和组织光学参数测量中具有极其重要的意义。文章提出了一种差分调制激光光谱技术,将经过生物组织后的散射光与参考光的光程差转换为光谱信号的频率特征,通过相敏检测技术将不同频率的信号进行分离,从而实现生物组织散射光的光程分离。文章分析了差分调制激光光谱的机理及信号的谱特征,并基于文献中的生物组织散射光的光程分布,从理论上讨论了差拍信号的谱特征,即光源调制速率一定时,光谱信号中的主频成分位置只与散射光和参考光的光程差有关;生物组织对光信号的衰减系数会影响光谱信号中频率成分的能量强度分布。分析结果表明,差分调制激光光谱能对生物组织的光谱信号进行光程分离,从而实现生物组织的单光程光谱检测。