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.

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.

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.

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.

Active Noise Control for Vehicle Exhaust Noise Reduction

An active noise control (ANC) method was developed for exhaust noise reduction for medium-duty diesel trucks. A modified variable step size least mean squares (LMS) algorithm was used for the controller in a variable environment that considered the vehicle's acceleration characteristics. The variable step size time-based synchronized filtered-x LMS method (SFX-TB) used an adaptive algorithm that was more efficient than the conventional filtered-x LMS algorithm. The simulation and the experimental tests show that the control trackability and stability provided by the algorithm during acceleration enable the ANC system to effectively reduce the vehicle exhaust noise.

Active control of intermittent noise in a room

Activc Noisc Control (ANC) systcm formed of a corner microphone-amplifier-loudspeaker system has been shown cffcchve to rcduce the reverberant noise in a room bascd on the normal-mode-canccling principle, and the theory and practicc of such has also been clarified. But steady state noisc are considered only in the past, and few cascs arc stable noise sources, and there is time that cven the stable noise sources are started or stopped. Any change of the noise source will excite transient in thc ANC system,which might have unfavorab1c effect on the application of thc ANC system. It is desirable to have a good knowledge of the transient behavior on thc ANC system in order to effect a better utilization of it. It is the purpose of this investiga tion to clarify the transient behavior of the ANC system in a room and the influence on its acoustics.

Active control of interior noise within an irregular enclosure under the cooperation of point force and Incident wave

A new modeling method is developed for the active control of interior noise within an irregular three-dimensional cavity under the cooperation of point force and incident wave. The validity of this method is verified by a regular cuboid enclosure. With global and local performance functions, good results are obtained in the active control of noise within the irregular enclosure according to numerical investigations.

Control strategies for aircraft airframe noise reduction

With the development of low-noise aircraft engine, airframe noise now represents a major noise source during the commercial aircraft＇s approach to landing phase. Noise control efforts have therefore been extensively focused on the airframe noise problems in order to further reduce aircraft overall noise. In this review, various control methods explored in the last decades for noise reduction on airframe components including high-lift devices and landing gears are summarized. We introduce recent major achievements in airframe noise reduction with passive control methods such as fairings, deceleration plates, splitter plates, acoustic liners, slat cove cover and side-edge replacements, and then discuss the potential and control mechanism of some promising active flow control strategies for airframe noise reduction, such as plasma technique and air blowing/suction devices. Based on the knowledge gained throughout the extensively noise control testing, a few design concepts on the landing gear, high-lift devices and whole aircraft are provided for advanced aircraft low-noise design. Finally, discussions and suggestions are given for future research on airframe noise reduction.

A numerical study of noise reduction in ducts with flow by anti-sound

Using the measures adopted in fluid mechanics, a numerical method of noise reduction in duct with flow by anti-sound is established, in which a mathematical anti-sound model is deduced strictly. Several numerical examples are given in the cascs of backward and forward sound propagation to illustrate the influence of anti-sound on sound field in duct and to discuss the effects of intensity and phase angle of anti-sound sources, and the effect of flow velocity.It is shown that noise reduction by anti-sound does have a bright prospect in engineering applications.