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200 kW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10~35 dB。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)。     

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)。      

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。      

一种改进的选频有源噪声控制算法

提出了一种改进的选频有源噪声控制(FSFANC)算法。 一个FSFANC系统通过在信号输入通道中引入选频滤波器(FSF)选择一根待消除的谱线进行处理,多个FSFANC系统可以独立并行工作。本算法采用只含两个系数的有限冲击响应(FIR)结构对次级通道、初级通道、选频滤波器、控制滤波器等有关模块进行建模。理论分析和实验结果表明,当FSF中心频率一定时,即便噪声谱线频率与其有几赫兹的偏差系统也依然保持稳定。本算法结构简单,计算量小,收敛速度快,稳定性高,克服了现有FSFANC算法对频率偏差要求过于严格的限制。     

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。     

有源抗噪声护耳器H2/H∞优化方法研究

采用固定系数滤波器和自适应滤波器相结合来实现一种有源抗噪声护耳器系统。固定系数滤波器除了降低宽带噪声,其最主要的作用在于减小次级通道的不确定性。固定系数滤波器和次级通道滤波器都采用H_2/H_∞优化方法设计得到。仿真和实验结果表明:固定系数滤波器提高了自适应算法的稳定性,护耳器系统在宽带和周期性噪声环境中都取得了比较好的降噪效果。     

空间有源消声实验研究

本文分别在半声室和普通房间进行有源消声实验，证明了作者以前提出的算法是收敛的，稳定的，以此算法构成的多通道有源消声系统对直达声和混响声都能进行了有效的控制。     

有源头靠中一种分布式虚拟传声器优化方法

有源降噪头靠系统中,远程虚拟传声器技术能够解决控制点处与误差传声器处降噪量不匹配的问题。在实际应用中,多通道虚拟传声器技术存在收敛速度慢和运算复杂度高等问题。针对这个问题,本文通过重新设计远程虚拟传声技术的离线优化过程,提出一种分布式远程虚拟传声器技术优化方法。该方法将虚拟次级通路矩阵作对角化限制,同时对观测传递函数矩阵进行联合寻优,以实现一种分布式的更新算法。有源降噪头靠实验结果表明,所提算法能够有效降低远程虚拟传声器技术算法的运算复杂度,并且提升了算法的收敛速度。     

有源头靠系统中次级声源和控制电路的参数优化研究

在有源头靠系统中,针对次级声源和控制电路两部分对模拟反馈有源控制系统(ANC)参数进行优化。为了达到更好的噪声抑制效果,次级声源的有效辐射频带应和待控制噪声的主要频谱相近,在使用电动扬声器作为次级声源时,其谐振频率应在要控制噪声频谱的下端。在优化控制电路参数时,根据经典控制理论提出合适的目标函数,通过差分演化算法进行优化。在有源头靠系统中,可通过适当调整两通道间距离,或将两通道间耦合纳入参数优化算法中,以保证系统稳定性和抑制"水床效应"的影响。模拟和实验表明两种方法各有利弊。在实际应用中需根据不同需要采用不同的优化方法。     

基于无限脉冲响应滤波器的自适应滤波E型有源噪声控制算法

相对于有限脉冲响应(FIR)滤波器,无限脉冲响应(ⅡR)滤波器由于其本身自有的零-极点结构,能以较低的阶数即可与系统模型匹配。因此在有源噪声控制(ANC)中,使用ⅡR滤波器可以大大节省计算量并能提高系统效率。自适应滤波U型最小均方差(FULMS)算法是目前常用的基于ⅡR滤波器的有源噪声控制算法,但该算法却不能保证全局收敛,这大大限制了该算法在有源噪声控制中的应用。本文提出一种新的基于ⅡR滤波器的自适应有源噪声控制算法——滤波E型最小均方差算法,该算法计算量相对于FULMS算法仅略有增加,但具有良好的全局收敛性,仿真结果表明该算法具有良好的降噪效果。     

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.     

Robust active control of broadband noise in finite ducts

This study focuses on robust active control of broadband noise in finite ducts. Our analytical and experimental studies suggest the existence of several technical flaws in the path models of conventional active noise control (ANC) systems. These are sensitivity of the path model with respect to boundary conditions, and nonminimum phase (NMP) secondary and reference paths. For finite ducts with small cross sections, the traveling wave model (TWM) may be adopted to find an effective solution to these problems and lead to a robust ANC system. Since many practical "noisy" ducts are finite with small cross sections, the proposed ANC has many practical applications. Its robustness and ability to suppress broadband noise will be explained theoretically and verified experimentally.     

A hybrid active noise controller for finite ducts

A hybrid active noise controller (ANC) is proposed to solve some existing problems, which are related to the non-minimum phase (NMP) path models between uncollocated sensors and actuators in many ANC systems. For hybrid ANC schemes, the NMP path causes design difficulties to both feedforward and feedback control. These problems can be solved effectively by adding an extra actuator in the ANC system. A new design procedure is presented to take the greatest advantage of the extra actuator. Theoretical analysis and experimental results are presented to show the improved performance of the proposed ANC.     

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.     

RETRACTED: A Hybrid Nonlinear Active Noise Control Method Using Chebyshev Nonlinear Filter

Investigations into active noise control (ANC) technique have been conducted with the aim of effective control of the low-frequency noise. In practice, however, the performance of currently available ANC systems degrades due to the effects of nonlinearity in the primary and secondary paths, primary noise and louder speaker. This paper proposes a hybrid control structure of nonlinear ANC system to control the non-stationary noise produced by the rotating machinery on the nonlinear primary path. A fast version of ensemble empirical mode decomposition is used to decompose the non-stationary primary noise into intrinsic mode functions, which are expanded using the second-order Chebyshev nonlinear filter and then individually controlled. The convergence of the nonlinear ANC system is also discussed. Simulation results demonstrate that proposed method outperforms the FSLMS and VFXLMS algorithms with respect to noise reduction and convergence rate.     

Secondary actuation and error sensing for active acoustic structure

A typical approach to active control of sound radiation or transmission from vibrating structures involves active structural acoustic control (ASAC) and active noise control (ANC), which introduce respectively force input and compacted sound source to apply on or be close to the vibrating structure. However, for the ASAC approach, arrangement for secondary force and error sensor is heavily dependent upon the properties of the primary structure and acoustical space; for the ANC approach, a large number of compacted secondary sources are required. Hence, in this paper, based on distributed secondary sound source and near-field error sensor, active acoustic structure is proposed to construct adaptive or smart structure as a versatile module or element for controlling sound radiation or transmission at low frequencies. First, a theoretical model based on a minimization of the total sound radiation from the primary and secondary panel is established, after which, taking into consideration the relationship between the vibration modes pattern and sound radiation characteristics for secondary panels, optimal arrangement for the secondary panels is examined in detail. Finally, a near-field pressure-based error sensing approach is presented, based on two kinds of object function, and active control of sound radiation is performed.     

Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

The FXLMS algorithm, which is extensively used in active noise control, exhibits frequency dependent convergence behavior. This leads to degraded performance for time-varying and multiple frequency signals. A new algorithm called the eigenvalue equalization filtered-x least mean squares (EE-FXLMS) has been developed to overcome this limitation without increasing the computational burden of the controller. The algorithm is easily implemented for either single or multichannel control. The magnitude coefficients of the secondary path transfer function estimate are altered while preserving the phase. For a reference signal that has the same magnitude at all frequencies, the secondary path estimate is given a flat response over frequency. For a reference signal that contains tonal components of unequal magnitudes, the magnitude coefficients of the secondary path are adjusted to be the inverse magnitude of the reference tones. Both modifications reduce the variation in the eigenvalues of the filtered-x autocorrelation matrix and lead to increased performance. Experimental results show that the EE-FXLMS algorithm provides 3.5-4.4 dB additional attenuation at the error sensor compared to normal FXLMS control. The EE-FXLMS algorithm's convergence rate at individual frequencies is faster and more uniform than the normal FXLMS algorithm with several second improvement being seen in some cases.     

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.