Abstract Active Noise Control Systems Research Articles

Active Noise Control Algorithm with Saturated Actuator

Active noise control system has received its attention in various technical field such as headphone, motor vehicle, etc. Meanwhile, filtered-x least mean square (FxLMS) algorithm is conventional linear algorithm used in active noise control system. It assumes that acoustic path from the noise source and control source to target area are linear. However, in actual system, the secondary path including a D/A converter, an amplifier, and an actuator may exhibits nonlinear distortion like saturation effects. To cope with this nonlinear effects, functional link artificial neural network (FLANN) has been proposed. FLANN uses nonlinear function expansion filter with FxLMS based control algorithm to control the nonlinear effect. In this paper, noise reduction performance and convergence speed are improved by modifying the conventional FLANN algorithm by decoupling the linear and nonlinear part of noise signal.

Experimental investigation on the potential of the Feedback Fx-LMS Active Noise Control technology for use in industrial generator sets

Active Noise Control (ANC) has been considered a promising technology for the abatement of acoustic noise from the mid-20th century. Feedback and Feedforward ANC algorithms, based on the destructive interference principle applied to acoustic waves, have been developed for different applications, depending on the spectrum of the noise source. Feedback ANC algorithms make use of a single control microphone to measure an error signal which is then employed by an adaptive filter to estimate the noise source and generate an opposite-phase control signal. The Fx-LMS (Filtered-X Least Mean Square) algorithm is mostly adopted to update the filter. Feedback ANC systems have proven to be effective for the abatement of low-frequency quasi-steady noises; however, different challenges must be overcome to realize an effective and durable system for high-temperature application. This paper aims at experimentally assessing the feasibility of a Feedback Fx-LMS ANC system with off-line Secondary Path estimation to be used in mid-size diesel gensets for the reduction of the exhaust noise. Several solutions are proposed, including the mechanical design, the development of the Fx-LMS algorithm in the LabVIEW FPGA programming language, and the key features required to prevent parts from thermal damage and fouling. The developed prototype was implemented on a 50-kW diesel genset and tested in a semi-anechoic chamber. The noise abatement inside the exhaust pipe and at different measurement points around the machine was evaluated and discussed, showing good potential for improving the acoustic comfort of genset users.

Quantum-behaved particle swarm optimization-based active noise control system with timing varying path

Active noise control systems can effectively suppress the impact of low-frequency noise and they have been applied in many fields. Recently, the evolutionary computation algorithm-based active noise control system has attracted considerable attention. To improve the noise reduction performance of the evolutionary computation algorithm-based active noise control system and solve the problem that the system cannot converge again when the path abruptly changes in steady state, we propose the path abruptly change-quantum-behaved particle swarm optimization algorithm. We apply quantum-behaved particle swarm optimization, a global optimization algorithm, to the active noise control system to improve noise reduction performance. In addition, the scheme of detecting the abrupt path change in steady state and performing re-convergence processing is designed to effectively address the problem that the system cannot regain convergence after a path change in steady state. The simulation study demonstrates that the proposed algorithm can efficiently improve noise reduction performance, accurately detect the path change, and re-converge to new global optimization.

Role of Acoustic Properties in Biomedical Active Noise Control

Active noise control (ANC) systems are tailored for user-specific scenarios which are required in biomedical applications due to the physical restrictions in the placement of sensors and actuators. This study examines the role of spectral flatness of acoustic channels and room reflection coefficients in ANC performance. Each room has a unique characteristic response in transforming a source signal. By employing preliminary measurements and numerical simulation, the authors show that improved noise control is possible by optimizing room reverberation and spectral flatness of the secondary acoustic channel. This result has potential application in improving existing ANC systems in biomedical applications like fMRI.

Exploiting the Underdetermined System in Multichannel Active Noise Control for Open Windows

Active noise control (ANC) is a re-emerging technique to mitigate noise pollution. To reduce the noise power in large spaces, multiple channels are usually required, which complicates the implementation of ANC systems. In this paper, we separate the multichannel ANC problem into two subproblems, where the subproblem of computing the control filter is usually an underdetermined problem. Therefore, we could leverage the underdetermined system to simplify the ANC system without degrading the noise reduction performance. For a single incidence, we compare the conventional fully-coupled (pseudoinverse) multichannel control with the colocated (diagonal) control method and find that they can achieve equivalent performance, but the colocated control method is less computationally intensive. Furthermore, the underdetermined system presents an opportunity to control noise from multiple incidences with one common fixed filter. Both the full-rank and the overdetermined optimal control filters are realized. The performance of these control methods was analyzed numerically with the Finite Element Method (FEM) and the results validate the feasibility of the full-rank and overdetermined optimal control methods, where the latter could even offer more robust performance in more complex noise scenarios.

FXECLMS Algorithm for Active Acoustic Windows: an Experimental Report

Active noise control (ANC) systems have become attractive solution for controlling the environmental noise in open windows. However, few works have demonstrated the benefits of using ANC systems in active acoustic windows since their implementation depends on several variables, such as the control source configuration (quantity and position of speakers), the adaptive control algorithm and the computational capabilities of the embedded devices. Specifically, the computational complexity of the adaptive control plays an important role in the development of practical real-timeANC applications. Until date, several works have presented theoretical models for ANC systems. Nevertheless, they do not consider the computational capabilities of the embedded devices to efficiently implement their adaptive algorithms, which limits its use in practical ANC applications. This paper presents for the first time a multichannel adaptive algorithm based on a filtered-x error coded least mean square (FXECLMS) and its efficient implementation to be used in an open-window ANC system. From the experimental results, we discuss the limitations, challenges and provide potential solutions in practical ANC implementations using advanced embedded devices.

The Design of Active Noise Control System in Power Transformer

Active noise control system on power equipment is designed. The paper gives overall analysis of the structure of the system. Adaptive control algorithm of control system is designed and simulated by CCS3.3. With other parameters of the system fixed, control effect of the system is analyzed by changing the filter order. As can be seen from the experimental effect, good control effect can be obtained when appropriate parameters are selected.

Hammerstein Nonlinear Active Noise Control with the Filtered-Error LMS Algorithm

Abstract Active Noise Control (ANC) of noise transmitted through a vibrating plate causes many problems not observed in classical ANC using loudspeakers. They are mainly due to vibrations of a not ideally clamped plate and use of nonlinear actuators, like MFC patches. In case of noise transmission though a plate, nonlinerities exist in both primary and secondary paths. Existence of nonlinerities in the system may degrade performance of a linear feedforward control system usually used for ANC. The performance degradation is especially visible for simple deterministic noise, such as tonal noise, where very high reduction is expected. Linear feedforward systems in such cases are unable to cope with higher harmonics generated by the nonlinearities. Moreover, nonlinearities, if not properly tackled with, may cause divergence of an adaptive control system. In this paper a feedforward ANC system reducing sound transmitted through a vibrating plate is presented. The ANC system uses nonlinear control filters to suppress negative effects of nonlinearies in the system. Filtered-error LMS algorithm, found more suitable than usually used Filtered-reference LMS algorithm, is employed for updating parameters of the nonlinear filters. The control system is experimentally verified and obtained results are discussed.

A novel feedforward active noise control structure with spectrum-tuning for residual noise

Active noise control (ANC) technology is becoming popular in consumer electronic products for audio applications. Typical ANC system aims primarily at reducing acoustic noise over the entire frequency band. However, human factors including diversity of individual listening preferences on spectral content and non-uniform characteristics of human hearing response in frequency domain require the capability of tuning the residual noise spectrum in ANC system. In this paper, we propose a new feedforward ANC structure featuring spectrum-tuning of the residual noise. Analysis shows that this new system has good tuning performance and little influence on system adaptation. Simulation results verify the effectiveness of the proposed system.

A Control Source Structure of Single Loudspeaker and Rear Sound Interference for Inexpensive Active Noise Control

Active noise control systems of simple ducts are investigated. In particular, open‐loop characteristics and closed‐loop performances corresponding to various structures of control sources are compared based on both mathematical models and experimental results. In addition to the standard single loudspeaker and the Swinbanks′ source, we propose and examine a single loudspeaker with a rear sound interference as a novel structure of control source, where the rear sound radiated from the loudspeaker is interfered with the front sound in order to reduce the net upstream sound directly radiated from the control source. The comparisons of the control structures are performed as follows. First, the open‐loop transfer function is derived based on the standard wave equation, where a generalized control structure unifying the three structures mentioned above is considered. Secondly, by a comparison of the open‐loop transfer functions from the first principle modeling and frequency response experiments, it is shown that a certain phase‐lag is imposed by the Swinbanks′ source and the rear sound interference. Thirdly, effects on control performances of control source structures are examined by control experiments with robust controllers.

Effects of Cross-Sectional Dimensions on Active Noise Control in Rectangular and Round Ducts

Active noise control (ANC) works best to reduce low frequency noise. Because many industrial noise sources are broadband, ANC may be used more if it can be successfully applied to higher frequency ranges. This study explored one method to increase ANC effectiveness at higher frequencies. ANC is particularly useful in hard-walled ducts where plane waves propagate. Higher order mode waves are much more difficult to control. Basic acoustic principles dictate that the cut-on frequency at which higher order modes will first begin to eclipse simple plane waves in a duct will be determined by the cross-sectional geometry of the duct. The lowest frequency for higher order modes increases as duct diameter decreases; therefore the range of frequencies where plane waves dominate will be greater and effective control using ANC will be better as duct diameter decreases. The result is that somewhat higher frequencies can be controlled with ANC for smaller diameters. Below the first higher order mode cut-on frequency for the largest size studied, there should be little difference in ANC effectiveness between the duct sizes. To test those suppositions, a commercially available ANC system was used to reduce random noise in rectangular and round ducts having different diameters. Results showed that insertion loss (IL) ranged from 5 dB to 29 dB in frequencies ranging from 40–1000 Hz and varied inversely with cross-sectional size as expected. There was no difference in IL below 280 Hz (p = 0.7751) between the different diameter ducts. There was a significant difference between duct diameters above 280 Hz (p < 0.0001). The same tests were conducted on a rectangular duct with one cross-sectional dimension fixed and one varied at seven different sizes. Results showed similar IL from 5 dB to 29 dB that varied inversely with size.

Simultaneous optimization of the sensor and actuator positions for an active noise and/or vibration control system using genetic algorithms, applied in a Dornier aircraft

Active noise control (ANC) became in the last decade a very popular technique for controlling low‐frequency noise. The increase in its popularity was a consequence of the rapid development in the fields of computers in general, and more specifically in digital signal processing boards. ANC systems are application specific and therefore they should be optimally designed for each application. Even though the physical background of the ANC systems is well‐known and understood, tools for the optimization of the sensor and actuator configurations of the ANC system based on classical optimization methods do not perform as required. This is due to the nature of the problem that allows the calculation of the effect of the ANC system only when the sensor and actuator configurations are specified. An additional difficulty in this problem is that the sensor and the actuator configurations cannot be optimized independently, since the effect of the ANC system is directly involved in the combined sensor and actuator configuration. For the solution of this problem several intelligent techniques were applied. In this paper the successful application of a genetic algorithm, an optimization technique that belongs to the broad class of evolutionary algorithms, is presented.

A Modern Control Approach to Active Noise Control

Active noise control systems currently in use and/or described in the research literature are typically based on adaptive signal processing theory or, equivalently, adaptive feedforward control theory. This paper presents a modern control approach to the problem of active noise cancellation in a three-dimensional space. The controller is designed based on a direct self-tuning regulator. Two forms of adaptive control, namely, pole placement and minimum variance controls are considered and compared in simulation. An implementation of the adaptive minimum variance controller is used to successfully attenuate a harmonic disturbance in a laboratory setting.