Active Cancelation of Acoustic Noise in Waveguides by Standard Control Task Decision Usage

Cybernetic decision variants were analyzed in order to use for physical task of active noise cancelation. 10 dB mean active noise cancellation is demonstrated in two decades frequency band by usage of cybernetic decision for acoustical duct physical scale model. The used decision was found on minimization of acoustical field power transfer function from the beginning of waveguide to their end.

Real-Time Detection of Unstable Control Loop Behavior in a Feedback Active Noise Cancellation System for In-Ear Headphones

Active noise controls are used in a wide field of applications to cancel out unwanted surrounding noise. Control systems based on the feedback structure however have the disadvantage that they may become unstable during run-time due to changes in the control path—in this context including the listener’s ear. Especially when applied to active noise cancellation (ANC) headphones, the risk of instability is associated with the risk of harmful influence on the listener’s ear, which is exposed to the speaker in striking distance. This paper discusses several methods to enable the analysis of a feedback ANC system during run-time to immediately detect instability. Finally, a solution is proposed, which identifies the open loop behavior parametrically by means of an adaptive filter to subsequently evaluate the coefficients regarding stability.

Adaptive ANFIS-based filter for active control of sinusoidal primary noise in nonlinear path

Linear active noise control (ANC) system is promising in suppressing broadband and narrowband noise in a linear acoustic site.However,in some situations,the acoustic systems are nonlinear which make the primary noise being nonlinear distortion at the canceling point,and the linear ANC system maybe can not work well for these cases.This paper presents an adaptive network-based fuzzy inference system (ANFIS)-based nonlinear filter for active noise control,which is expected to be successfully applied to situations with nonlinear distortion.In the proposed adaptive control algorithm,the parameters are updated by gradient descent method.In the simulations,the secondary-path FIR model coefficients are estimated in advance by off-line system identification method,and one case for sinusoidal primary noise with nonlinear distortion is presented,which verifies the effectiveness of the proposed system in suppressing sinusoidal noise generated by rotating machines,e.g.,engines in vehicles.

Active Noise Control of the Heavy Truck Interior Cab

In order to control the noise of the heavy truck interior cab effectively, the active noise control methods are employed. First, an interior noise field test for the heavy truck is performed, and frequencies of interior noise of this vehicle are analyzed. According to the spectrum analysis of acquired noise signal, it is found out that the main frequencies of interior noise are less than 800Hz. Then the least squares lattice （LSL） algorithm is used as signal processing algorithm of the controller and a closed-loop control DSP system, based on TMS 320VC5416, is developed. The residual signal at driver＇s ear is used as feedback signal. Lastly, the developed ANC system is loaded into the heavy truck cab, and controlling the noise at driver＇ s ear for that truck at different driving speeds is attempted. The noise control test results indicate that the cab interior noise is reduced averagely by 0.9 dBA at different driving speeds.

Feed-Forward Active Noise Control System Using Microphone Array

Feedforward active noise control(ANC) system are widely used to reduce the wide-band noise in different application. In feedforward ANC systems, when the noise source is unknown, the misplacement of the reference microphone may violate the causality constraint. We present a performance analysis of the feedforward ANC system under a noncausal condition. The ANC system performance degrades when the degree of noncausality increases. This research applies the microphone array technique to feedforward ANC systems to solve the unknown noise source problem. The generalized cross-correlation(GCC) and steering response power(SRP) methods based on microphone array are used to estimate the noise source location.Then, the ANC system selects the proper reference microphone for a noise control algorithm. The simulation and experiment results show that the SRP method can estimate the noise source direction with 84% accuracy. The proposed microphone array integrated ANC system can dramatically improve the system performance.

Analysis and active control of low frequency booming noise in car

For Lightweight body,sound radiation and sound insulation performance have negative effects on interior noise by the deterioration of local stiffness and modality.So the research on the active control of vibration and noise for car body panels is useful for engineering.Analysis and active control of booming noise in car is researched by using a new active damping vibration reduction technology named smart constrained layer damping(SCLD).According to the vibration characters of body roof,an optimal placement of actuators is distributed.Based on dSPACE hardware in loop environment,an adaptive active control system is designed.Selecting vibration signals of engine mounting point as the reference input of adaptive controller,an active control experiment of booming noise for mini-car is carried out.Experimental results show that,when the engine speed is at 3700 RPM and4250RPM,the interior booming noise decreases 4.2dB(A),and 3.5dB(A) separately.It proposes new methods and techniques for intelligent control of car body NVH in the future.

Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.

Simulation Study of Active Noise Control in Wind Turbines Using FxLMS Adaptation Algorithm

Utility scale wind turbines produce a significant amount of noise which has been identified as one of the most critical challenges to the widespread use of wind energy. Aerodynamic noise caused primarily by the interaction of the boundary layer and (or) the upstream atmospheric turbulence with the trailing edge of the blade has been identified as the most dominant source of noise in wind turbines. The authors here propose an active noise control system based on the FxLMS algorithm which can achieve suppression of noise from a modern wind turbine. Two types of noise sources have been simulated: monopole and dipole. The results of the active noise control algorithm are validated with simulations in MATLAB. The agreement between the results shows the far impact of active noise control techniques will have in future wind turbines.

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.

Dynamic Active Noise Control of Broadband Noise in Fighter Aircraft Pilot Helmet

This paper presents the development of a dynamic Active Noise Control(ANC)algorithm aimed towards redu-cingthe broadbandnoiseinside the helmet earcups ofafighter aircraftpilot helmet.The dynamicANC involves a Variable Step-Size Griffiths(VSSG)FxLMS algorithm to attenuate noise entering directly through helmet,a LMS based adaptive noise canceller to attenuate noise entering through the pilot microphone,and energy detectors for failure protection and optimized battery power usage.The algorithms are implemented on Texas Instruments’TMS320C6748 processor and are tested in a helmet ANC experimental setup.

SMART STRUCTURES USING PIEZOELEMENTS FOR ACTIVE VIBRATION AND NOISE SUPPRESSION IN AVIATION AND AEROSPACE

具有减振降噪功能的压电智能结构是智能材料与结构的一个重要分支。在航空航天领域存在一些典型结构，如飞机机舱、空间站、卫星太阳能帆板和通讯天线以及直升机旋翼等，其振动与辐射噪声造成很多不利影响。为了研究这些结构的振动与噪声控制方法，制作了几个实验模型如大型薄壁复合材料圆桶、柔性梁、钢架及旋翼系统模型，通过压电传感器、驱动器布置数量和位置的优化，采用不同的控制算法，在基于个人计算机的测控平台上进行了振动控制实验，取得了明显的减振降噪效果。

Application of system identification in a practical active noise control system

Noise pollution has become increasingly severe around the world due to fast urbanization. How to soundproof windows from outside noise is of significant interest for both academia and industry. This paper reports an experimental implementation of normalized minmax active noise control (ANC) algorithm on an open window system, where identifying the model of acoustic sound paths plays a central role. By doing this, traffic noise is attenuated by the ANC system, leading to a relatively quiet indoor environment, while the natural lighting and ventilation functions of a window are remained. Our experiments show that an average of 19 dB(A) noise reduction is achieved.

Ear Field Adaptive Noise Control for Snoring:An Real-time Experimental Approach

In this paper, an active noise control(ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive least mean square(LMS)algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square(FXLMS) algorithm.Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer's bed partner.

车内单座椅局部区域有源噪声控制研究

目前,汽车局部区域降噪主要通过有源降噪头枕来降低人耳处的噪声,但乘客的移动会影响降噪效果.结合人头跟踪系统可解决这一问题,代价是增加系统的复杂性和成本.以车门扬声器为次级声源,在副驾驶位置乘客头部周围较大的区域进行局部降噪,并优化误差传感策略提升其降噪性能.首先,建立轻度阻尼边界的闭空间声场有限元模型;然后,基于该模型研究了某一局部区域内取得3 dB降噪效果的频率上限、误差点数量和位置对降噪效果的影响以及误差点布放的优化问题;最后,在典型城市道路上进行不同车速下的有源噪声控制实验.结果表明,车速为50,60和80 km·h^(-1)时,副驾驶头部区域内(0.4 m×0.4 m×0.2 m)3 dB降噪的频率上限约为370 Hz,误差点位置对降噪效果有较大影响.采用遗传算法优化误差点选择可提高降噪性能,使用12个优选误差点即可达到使用75个均匀布放误差点的降噪效果.

汽车冷却风扇噪声主动控制仿真及声品质评价

以汽车冷却风扇噪声为研究对象,基于采集的噪声生成具有不同音调特性的模拟噪声,利用改进的音调度模型计算音调度,使用等级评分法对生成的模拟噪声进行主观评价实验。根据音调特性十分明显的旋转噪声频率与风扇转速密切相关的特点,提出以风扇转速信号来构造次级声源参考信号进行主动噪声控制。最后建立并联型灰色神经网络模型并检验降噪效果。结果表明,冷却风扇噪声的音调特性是影响感知烦恼的重要因素之一,通过有源噪声控制能有效降低窄带噪声峰值从而降低音调度。引入并联型灰色神经网络进行预测的平均相对误差为2.86%,降噪后烦恼度有较好的改善。

Experimental research of active vibration and noise control of electrically controlled rotor

Electrically Controlled Rotor(ECR),also called as swashplateless rotor,applies blade pitch inputs via trailing-edge flaps system instead of traditional swashplate mechanism.In addition to primary control,rotor vibration reduction and noise alleviation are also achievable via applying higher harmonic control inputs with the trailing-edge flaps.In this paper,the feasibility of ECR to reduce vibration and noise actively is verified experimentally.Firstly,the test scheme of ECR active vibration and noise control is proposed,and the ECR test platform is modified according to the test scheme.Then,an adaptive control algorithm based on Kalman filter is developed.Lastly,hover and wind tunnel tests is performed to verify the feasibility of ECR active vibration and noise control.The results demonstrate that the ECR are effective for reducing rotor vibration and noise simultaneously.In the hover condition,the ECR can reduce the in-plane hub vibration by 42%and the inplane noise by 4dB.In wind tunnel condition,ECR can reduce the hub vibration by 75%and the BVI noise by 3dB.

基于活动性检测动态估计噪声的心音降噪算法

针对基于小波分解和最优改进对数幅度谱估计的心音降噪算法存在噪声残留和心音失真的问题,提出一种基于心音活动性检测(HSAD)动态估计噪声的心音降噪算法。通过设计的HSAD判断当前心音帧是否为基础心音帧(FHS),根据判断结果分别采用改进最小值控制递归平均(IMCRA)算法和递归平滑算法对噪声功率进行动态估计与更新,采用非因果先验信噪比,实现心音信号的降噪。实验结果表明,提出算法能更好在提升降噪性能的同时,降低FHS的失真。

基于随机系数Logit模型的专利价值评估研究——以主动降噪技术为例

[研究目的]从分析专利价值入手,通过经济学研究方法围绕专利侵权损害赔偿的标准进行定量研究,为评估专利价值提供有意义的知识增量。[研究方法]基于实证产业组织理论,采用随机系数Logit模型,以无线蓝牙耳机主动降噪(ANC)技术作为研究对象,构建该技术遭受侵权的反事实情形来估计经济指标变化,由此评估专利价值及侵权赔偿比例。[研究结论]专利侵权企业的行为产生了反竞争效应,提升了企业垄断势力,挤占了其他耳机企业的生存空间,也对潜在进入企业形成了进入威胁。蓝牙耳机价格中约有4.06%源于ANC专利标识。如果发生ANC专利侵权,赔偿额度应是侵权企业利润的2.6~2.8倍。该方法利用市场数据在均衡框架下评估专利价值,为相关研究提供了新方向。