基于响度控制的封闭腔有源噪声控制

传统有源噪声控制（ANC）通常是控制声压平方和最小，但声压与人耳对声音强弱的主观感觉并不完全一致。为了考虑人的主观听觉作用，在传统ANC系统中加入若干个响度滤波器，使其控制目标从声压转变为响度。从心理声学出发，建立了用于ANC的人耳听觉响度模型，给出了矩形封闭腔响度ANC模型以及基于FLMS算法的响度控制算法。仿真结果表明，与声压控制相比，基于响度控制的ANC系统的声压下降量稍小，但响度的减小量更大，具有更好的主观听觉效果。     

Modified-filtered-u LMS algorithm for active noise control and its application to a short acoustic duct

This paper presents a new adaptive algorithm for active noise control (ANC) that can be effectively applicable to a short acoustic duct, such as the intake system of an automobile engine, where the stability and fast convergence of the ANC system is particularly important. The new algorithm, called the modified-filtered-u LMS algorithm (MFU-LMS), is developed based on the recursive filtered-u LMS algorithm (FU-LMS) incorporating the simple hyper-stable adaptive recursive filter (SHARF) to ensure the control stability and the variable step size to enhance the convergence rate. The MFU-LMS algorithm is implemented by purely experimental ways, and is applied to active control of noise in a short acoustic duct, and is validated using two experimental cases of which the primary noise sources are a sinusoidal signal embedded in white noise and a chirp signal. The experimental results demonstrate that the proposed MFU-LMS algorithm gives a considerably better performance than other conventional algorithms, such as the filtered-x LMS (FX-LMS) and the FU-LMS algorithms.     

一种低复杂度快速收敛的窄带主动噪声控制系统

传统窄带主动噪声控制( ANC)系统的计算负荷与窄带噪声频带数量正相关,而且其收敛速度和降噪效果存在此消彼 长的关系。 为解决以上问题,首先基于滤波误差技术简化窄带 ANC 模型,使系统计算量与窄带噪声频带数量相互独立。 然后 通过自适应混合参数将两个简化的窄带 ANC 系统进行并行凸组合,其中一个系统拥有最快的收敛速度,另一个系统拥有较低 的稳态误差。 提出的系统不仅降低了传统窄带 ANC 系统的计算复杂度,而且在不牺牲降噪性能的情况下提升了系统收敛速 度。 实验结果表明,提出系统在不牺牲稳态误差的基础上,收敛时间缩短了 78% ,有效提升了系统收敛性能。     

管道复合主动噪声控制系统及其实现

为了提高管道噪声主动控制系统的性能,设计出基于TI公司的TMS320C30芯片作为控制器的实时管道复合噪声主动控制系统(简称ANC系统)。针对前馈ANC可实现较宽的降噪频带,但在实际复杂系统中不能完全满足参考传感器信号和噪声声源要紧密相关要求;而反馈ANC系统中,降噪效果不依赖于声场的相关性,但其降噪频带较窄的特点,设计出复合FXLMSANC系统。在某风机、通风管路系统上进行ANC试验的结果表明,应用复合FXLMSANC方法,能获得比单独使用前馈FXLMSANC算法或反馈FXLMSANC算法更好的降噪效果。     

次级声源安装角度对管道有源消声性能的影响研究

分别从理论和试验两个方面,对非适应和自适应两种管道有源消声系统中的次级声源安装角度对系统性能的影响进行了研究。结果表明,采用自适应结构具有明显的优越性。小的次级声源安装角度,可以优化有源消声系统的声波干涉条件,提高系统消声量,加快自适应有源消声系统收敛速度,并适当降低系统对次级声源的功率要求。对宽带有源消声系统而言,可以提高次级声源的指向性,减小系统存在的"声反馈"现象,提高控制系统的工作稳定性。最后,提出了几项实际工程设计原则。     

Short-term annoyance reduction evoked by active noise control method on turboprop regional aircraft cabin noise

Since the 2000s, the advancing global economy has increased the demand for turboprop regional aircraft, and various studies have been conducted to resolve aircraft noise-related problems. Despite the progress made by previous studies, turboprop regional aircraft still have a poor noise environment compared to other vehicles. In addition, although an application of active noise control (ANC) method had improved the noise environment of the cabin, none of studies were conducted in consideration of a relationship between the application of ANC method and the resulting change of an (short-term) annoyance. Therefore, in the current study, an annoyance reduction evoked by active noise control (ANC) methodology on a turboprop regional aircraft cabin noise was investigated in three experiments. In the first experiment, 50 participants estimated the perception limit of psychoacoustic parameters on aircraft interior noise to identify the cognitive characteristic of the noise. Furthermore, the noise reduction achieved by applying ANC was identified based on the empirical results of the second experiment. Finally, the third experiment examined the relationship between psychoacoustic parameters (loudness and sharpness) and annoyance with the assistance of 50 participants. As a result, the difference between the noise reduction and the annoyance reduction was identified. Furthermore, the degree of annoyance reduction of implementing ANC in cabin noise was identified.

     

基于TMS320C6713的去噪自适应滤波器硬件实现

我们每天都会受到音频噪音的影响,原始信息会受到周围环境噪声信号的污染。为此,本文研究了一个多抽头自适应去噪实时硬件系统,它利用TMS320C6713上实现的最小均方算法（LMs）来去除与音频相关的应用程序中接收到的不期望出现的噪声信号。文章首先介绍了最小均方算法的c语言实现并在CodeComposerStudio上进行仿真,最后在C6713上实现。考虑不同的音频输入,进行了三项实验来测试所设计的自适应去噪系统的效率。实验采用300、500、800、1000和3000Hz的音频信号及男性语音信号为输入的参考信号,持续检测信号中的噪声,直至将它全部去除。此外,还研究了与自适应去噪系统性能相关的收敛速度、滤波器安排顺序以及信噪比。实验结果表明,所设计系统其信噪比有很大的改善。     

主动噪声控制技术及其在车内噪声控制中的应用

主动噪声控制是集声学、自适应控制及数字信号处理等技术为一体的高新技术，已成为国内外噪声控制界的研究热点。基于主动噪声控制的Swinbanks多极子系统理论，证明了主动噪声控制技术适合于低频．1k的理论依据。阐述了决定主动噪声控制效果的决定因素及在车内噪声控制中应用的发展过程，并指出当前研究中需解决的问题和今后的研究方向。     

Quiet zone tuning in a non-ideal sound field

Most active noise control (ANC) systems are designed and analyzed in ideal sound fields, where ANC performances are predictable with acceptable accuracies. In many ANC applications sound fields are non-ideal with significant differences between real ANC performances and theoretical predictions. If one uses an ideal model to optimize locations of actuators or error sensors for an ANC system in a non-ideal sound field, the actual quiet zone is inevitably different from its theoretical prediction. It is desired that users of ANC systems can tune quiet zones by adjusting ANC configurations, such as locations of secondary sources or error sensors. Model-independent ANC (MIANC) systems are preferred for this purpose. In this study, a model-independent ANC system is improved, implemented and applied to create a quiet zone in a non-ideal sound field. Users of the system can adjust locations of actuators or error sensors to tradeoff between sizes of quiet zones and levels of noise attenuations. Experimental results are presented to demonstrate observations and effects of quiet zone tuning using the improved ANC system.     

一种稳健的窄带反馈型主动噪声控制系统

传统窄带反馈型主动噪声控制系统采用并型自适应滤波器结构,用于合成参考信号时,仍存在参考信号合成质量较差、 滤波器权值的初值设置难度高、应对非平稳窄带噪声的能力不足等问题。 为解决以上问题,通过引入高效的串并型自适应滤波 器结构来合成参考信号,提出新型的窄带反馈型主动噪声控制系统,改善参考信号合成质量,进而提升系统的整体降噪性能。 新型系统不仅有效解决了传统系统存在的参考信号合成质量较差的问题,还降低了滤波器权值的初值设置复杂度,同时还提升 了系统应对非平稳窄带噪声的能力。 实验结果表明,新型系统较传统系统的前后两部分的降噪量分别提升了 7. 89 和 9. 18 dB。 仿真和实验结果共同验证了提出的系统较传统系统具有更强的稳健性和降噪性能。     

利用多层感知神经网络对空调噪声的控制研究

提出一种神经网络自适应噪声主动噪声控制(ANC)的方法。把后传播学习算法的多层感知神经网络用来对空调进行 ANC。对在三维空间传播的宽频带空调噪声 ,利用多层感知神经网络的 ANC获得了良好降噪效果。     

A local active noise control system based on a virtual-microphone technique for railway sleeping vehicle applications

Low-frequency broadband noise generated on a railway vehicle by the wheel–rail interaction could be a big annoyance for passengers in sleeping cars. Low-frequency acoustic radiation is extremely difficult to attenuate by using passive devices. In this article, an active noise control (ANC) technique has been proposed for this purpose. A three-dimensional cabin was built in the laboratory to carry out the experiments. The proposed scheme is based on a Filtered-X Least Mean Square (FXLMS) control algorithm, particularised for a virtual-microphone technique. Control algorithms were designed with the Matlab-Simulink tool, and the Real Time Windows Target toolbox of Matlab was used to run in real time the ANC system. Referring to the results, different simulations and experimental performances were analysed to enlarge the silence zone around the passenger's ear zone and along the bed headboard. Attenuations of up to 20 and 15 dB(A) (re:20 μPa) were achieved at the passenger's ear in simulations and in experimental results, respectively.     

Active noise control using a distributed mode flat panel loudspeaker

A flat panel distributed mode loudspeaker (DML) has many advantages over traditional cone speakers in terms of its weight, size, and durability. However, its frequency response is uneven and complex, thus bringing its suitability for active noise control (ANC) under question. This paper presents experimental results demonstrating the effective use of panel DML speakers in an ANC application. Both feedback and feedforward control techniques are considered. Effective feedback control with a flat panel speaker could open up a whole range of new noise control applications and has many advantages over feedforward control. The paper develops a new control algorithm to attenuate tonal noise of a known frequency by feedback control. However, due to the uneven response of the speakers, feedback control is found to be only moderately effective even for this narrow-band application. Feedforward control proves to be most capable for the flat panel speaker. Using feedforward control, the sound pressure level can be significantly reduced in close proximity to an error microphone. The paper demonstrates an interesting application of the flat panel in which the panel is placed in the path of sound and effectively used to block sound transmission using feedforward control. This is a new approach to active noise control enabled by the use of flat panels and can be used to prevent sound from entering into an enclosure in the first place rather than the traditional approach of attempting to cancel sound after it enters the enclosure.     

New analytical model for the filtered-x least mean squares algorithm verified through active noise control experiment

This paper presents a new analytical model for the behavior of the Filtered-x LMS adaptive algorithm when applied to active noise control (ANC) in a finite duct. The new model is derived using a stochastic differential equation (SDE) approach. The theoretical predictions are verified through experimental results. The real-time system has been implemented using only I/O cards and a general purpose computer. Automation of the experimental setup allows the practical verification of the theoretical statistical model using Monte Carlo techniques. It is verified that the behavior of the algorithm is accurately predicted by the theoretical model.     

Adaptive frequency tuner for active narrowband noise control systems

The reference frequency error can significantly degrade the performance of the narrowband active noise control (ANC) system. This paper investigates the relationship between the reference frequency error and the performance of the narrowband ANC system, and presents an adaptive frequency tuner which can reduce the reference frequency error and improve the performance of the system. Effectiveness of the adaptive frequency tuner is validated by simulation results using experimental transfer functions.     

Gear fault diagnosis using active noise cancellation and adaptive wavelet transform

Acoustic signal from a gear mesh with faulty gears is in general non-stationary and noisy in nature. Present work demonstrates improvement of Signal to Noise Ratio (SNR) by using an active noise cancellation (ANC) method for removing the noise. The active noise cancellation technique is designed with the help of a Finite Impulse Response (FIR) based Least Mean Square (LMS) adaptive filter. The acoustic signal from the healthy gear mesh has been used as the reference signal in the adaptive filter. Inadequacy of the continuous wavelet transform to provide good time–frequency information to identify and localize the defect has been removed by processing the denoised signal using an adaptive wavelet technique. The adaptive wavelet is designed from the signal pattern and used as mother wavelet in the continuous wavelet transform (CWT). The CWT coefficients so generated are compared with the standard wavelet based scalograms and are shown to be apposite in analyzing the acoustic signal. A synthetic signal is simulated to conceptualize and evaluate the effectiveness of the proposed method. Synthetic signal analysis also offers vital clues about the suitability of the ANC as a denoising tool, where the error signal is the denoised signal. The experimental validation of the proposed method is presented using a customized gear drive test setup by introducing gears with seeded defects in one or more of their teeth. Measurement of the angles between two or more damaged teeth with a high level of accuracy is shown to be possible using the proposed algorithm. Experiments reveal that acoustic signal analysis can be used as a suitable contactless alternative for precise gear defect identification and gear health monitoring.     

A STUDY OF ACTIVE NOISE CANCELLATION IN DUCTS

An infinite impulse response (IIR) filter based on RLMS algorithm is used to control the sound propagated in a duct. The offline error path modification is also included in the algorithm in order to obtain a better result. Three different types of noise source, i.e. pure tone, dual sine and narrowband-limited noise, are considered. This controller not only has a strong effect on the noise reduction for pure tone and dual sine sound sources, but also reduces the narrowband-limited noise markedly. Further study on the reduction of the broad noise source is required however.     

一种含次级通道在线辨识的窄带主动噪声控制系统

分析了噪声危害设备产生的谐波噪声,特别是以500 Hz或600 Hz以下的低频成分为对象,介绍了主动噪声控制(ANC)技术的原理、意义及发展现状。在实际声学场所,由于控制系统易受初级噪声功率、残余噪声幅值等因素影响而不稳定。在分析控制系统收敛条件的基础上,通过对系统误差引入一个比例因子从而改进系统模型,并以一维管道为实验平台,基于高速数字信号处理器(DSP)设计了含次级通道在线辨识的主动噪声控制器。实验结果表明,在250 Hz左右的频段上能够达到16 dB的降噪效果。     

自适应有源消声的进展及趋势

对噪声控制的研究进展及发展趋势作了综述,将近几年来有源消声的消声系统、消声机理、控制器设计及算法等方面的现有研究成果进行了总结,介绍了一些较为成功的实例,对今后一段时期有源消声的主要发展方向做出了预测.     

LYAPUNOV TUNING OF THE LEAKY LMS ALGORITHM FOR SINGLE-SOURCE,SINGLE-POINT NOISE CANCELLATION

Least-mean square (LMS) algorithms, which are commonly used for adaptive feedforward noise cancellation, have performance issues related to insufficient excitation, non-stationary reference inputs, finite-precision arithmetic, quantisation noise and measurement noise. Such factors cause weight drift and potential instability in the conventional LMS algorithm. Here, we analyse the stability and performance of the leaky LMS algorithm, which is widely used to correct weight drift. A Lyapunov tuning method is developed to find an adaptive leakage parameter and adaptive step size that provide optimum performance and retain stability in the presence of measurement noise on the reference input of known variance. The method accounts for non-persistent excitation conditions and non-stationary reference inputs and requires no a priori knowledge of the reference input signal characteristics other than a lower bound on its magnitude or a minimum signal-to-noise ratio. The Lyapunov tuning method is demonstrated for three candidate adaptive leakage and step size parameter combinations, each of which is a function of the instantaneous measured reference input, measurement noise variance, and/or filter length. These candidates illustrate stability vs performance tradeoffs in the leaky LMS algorithm elicited through the Lyapunov tuning method. The performance of each candidate Lyapunov tuned algorithm is evaluated experimentally in a single source, single-point acoustic noise cancellation system.