Active Noise Control Applications Research Articles

A new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control systems

Infinite impulse response filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O( n 2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O( n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR filters to adaptive IIR filters. Comparison of the performance of the fast-array algorithm with that of Erikson’s FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.

Active noise control of magnetic resonance imaging scanner using inverse modeling technique.

In active noise control applications, internal model control (IMC) is a strategy to convert from feedback to feedforward control. In this configuration, the optimal solution of the controller will be the inverse model of the secondary path. However, the inverse model of the secondary path may not always exist. In fact, for the non‐minimal phase system, the inverse model is unstable. In this case, the non‐causal or delayed version of the inverse model will be employed. In general, this approach is not suitable for active noise control if the objective is to treat broadband noise. However, for harmonic signal control, this is not an issue. Magnetic resonance imaging (MRI), a procedure for medical diagnosis and biomedical research, generates undesirable levels of acoustic noise emission. The noise is normally dominated by clusters of harmonics throughout the audio spectrum. Due to its tonal nature, MRI noise control is a candidate for IMC. In this paper, an active noise control scheme using the inverse modeling technique is proposed and studied for pre‐recorded MRI noises obtained during operation of a 4T whole‐body MRI scanner. The recorded MRI noise is played back through a stereo system in a sound quality room and controlled using a headset equipped with the proposed active controller. The results demonstrate almost 20 dB reduction can be achieved.

Development and application of audio-integrated ANC system for infant incubators

This paper presents the application of audio-integrated active noise control (ANC) system for infant incubators. The integrated ANC algorithm is developed to reduce external harmful noises while playing healthy intrauterine sounds inside the incubators. Real-time experiments are conducted to evaluate the performance of an integrated system using a Giraffe incubator from GE Healthcare. The noise reduction achieved by ANC systems at uniformly-distributed three-dimensional locations inside the incubator is presented in tables and graphically. The single-channel ANC system is integrated with intrauterine sounds to mask residual noise and create a prenatal environment for the infants, and also enhance the performance of the incubator ANC system with time-varying secondary paths.

Neural filtered-U algorithm for the application of active noise control system with correction terms momentum

This paper introduces a novel neural filtered-U recursive least mean square (NFURLMS) algorithm and its corresponding weight updating method to the application of active noise control (ANC) system. Instead of the complex designing procedures, the proposed approach uses few mathematical transfer functions to design the ANC system. The correction terms momentum to avoid the premature saturation of back-propagation algorithm and the way to design the optimal learning rate are also included in the paper to improve the noise reduction performance. In addition, the proposed method protects ANC systems against unstable poles such as occur in conventional filtered-U design. Several simulation results show that the proposed method can effectively cancel the narrowband and broadband noise in an ANC system.

A novel design strategy for iterative learning and repetitive controllers of systems with a high modal density: Theoretical background

This paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems with a high modal density has several important drawbacks: the design procedure is complex, the controllers require much computational power and the robustness of the controllers is low. This paper describes a novel strategy to design noncausal ILC and RC filters, which is especially suited for high modal density systems. Since it does not require a parametric system model, the novel strategy avoids several drawbacks of the traditional techniques: no cumbersome parametric model estimation is required; the ILC and RC controllers are robust to small changes of the poles and zeros of the controlled system; and the complexity of the ILC and RC control filters is restricted. A crucial element in the proposed strategy is the noncausal filtering in the ILC and RC controllers, which requires the availability of a trigger signal to announce a new ILC trial or RC period in advance. A numerical validation on a simulation model proves the potential of the developed strategy.

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.

하이브리드 제어 알고리즘을 이용한 덕트내 능동소음제어

This study presents the active noise control of duct noise. The duct was excited by a steady-state harmonic and white noise force and the control was performed by one control speaker attached to surface of the duct. An adaptive controller based on filtered x LMS(FXLMS) algorithm was used and controller was defined by minimizing the square of the response of the error microphone. The assemble controller, which is called a hybrid ANC(active noise control) system, was combined with feedforward and feedback controller. The feedforward ANC attenuates primary noise that is correlated with the reference signal, while the feedback ANC cancels the narrowband components of the primary noise that are not observed by the reference sensor. Furthermore, in many ANC applications, the periodic components of noise are the most intense and the feedback ANC system has the effect of reducing the spectral peaks of the primary noise, thus easing the burden of the feedforward ANC filter.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feedforward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

Optimization of control source locations in free-field active noise control using a genetic algorithm

Control source locations in active noise control applications introduce a physical limit in the amount of attenuation achievable by the system. A genetic algorithm was developed to find the optimal control source locations for a primary source configuration in a free-field with a specified number of control sources. The optimal configuration of control sources around a single monopole primary source was shown to be a linear arrangement of the sources. This holds true for both two-dimensional as well as three-dimensional configurations. These results are presented for configurations using up to six control sources. The linear arrangement of control sources provides higher-order radiation characteristics than previously studied arrangements. Experimental verification has shown that a monopole primary source is controlled more effectively with a linear array of sources than sources surrounding the primary source for a broad frequency range. The source strength required from the control sources in each configuration is also explored.

Fast Affine Projection Algorithms for Filtered-x Multichannel Active Noise Control

In recent years, affine projection algorithms have been proposed for adaptive system applications as an efficient alternative to the slow convergence speed of least mean square (LMS)-type algorithms. Whereas much attention has been focused on the development of efficient versions of affine projection algorithms for echo cancellation applications, the similar adaptive problem presented by active noise control (ANC) systems has not been studied so deeply. This paper is focused on the necessity to reduce even more the computational complexity of affine projection algorithms for real-time ANC applications. We present some alternative efficient versions of existing affine projection algorithms that do not significantly degrade performance in practice. Furthermore, while in the ANC context the commonly used affine projection algorithm is based on the modified filtered-x structure, an efficient affine projection algorithm based on the (nonmodified) conventional filtered-x structure, as well as efficient methods to reduce its computational burden, are discussed throughout this paper. Although the modified filtered-x scheme exhibits better convergence speed than the conventional filtered-x structure and allows recovery of all the signals needed in the affine projection algorithm for ANC, the conventional filtered-x scheme provides a significant computational saving, avoiding the additional filtering needed by the modified filtered-x structure. In this paper, it is shown that the proposed efficient versions of affine projection algorithms based on the conventional filtered-x structure show good performance, comparable to the performance exhibited by the efficient approaches of modified filtered-x affine projection algorithms, and also achieve meaningful computational savings. Experimental results are presented to validate the use of the algorithms introduced in the paper for practical applications.

Active control of diffuse sound fields using generalized energy density.

In enclosures, the total acoustic energy density (ED) has been shown both theoretically and experimentally to be more spatially uniform than the squared pressure. The generalized energy density (GED) has even more uniform properties than the acoustic energy density. In active noise control applications, the standard approach taken is to minimize the squared pressure response in the field. However, the use of ED as the minimization quantity has been demonstrated to yield improved performance in low modal density acoustic fields, often resulting in improved global attenuation. For diffuse acoustic fields (high modal density), local “quiet zones” can be achieved, with the volume of this quiet zone typically being characterized as a sphere with a diameter of about one‐tenth of a wavelength when the squared pressure is minimized. It has been found that this performance can also be improved through the use of GED. By controlling GED instead of squared pressure, one cannot only increase the size of the quiet zone but also decrease the acoustic power added into the system. Results will be shown to illustrate the improved performance.

New IIR filter-based adaptive algorithm in active noise control applications: Commutation error-introduced LMS algorithm and associated convergence assessment by a deterministic approach

In this study, commutation error (CE) is defined in adaptive infinite impulse response (IIR) filter-based ANC systems. CE is subsequently introduced into a new residual error to develop a new LMS-based ANC algorithm in an aim to liberate the restriction of slow adaptation posed on traditional ANC algorithms. A new deterministic analysis based on a linear time-varying system is performed to investigate convergence properties of the developed algorithm: (1) An optimal step size for the fastest convergence rate can be derived. (2) Given a persistent excitation condition and a step-size constraint, we find that the algorithm is uniformly asymptotically stable. Computer simulations indeed demonstrate a greatly improved convergence rate and efficient ANC performance for the developed algorithm as compared with that using the conventional algorithms. Experimental results verify the enhanced ANC performance in real applications. These together support the new IIR filter-based adaptive algorithm that includes CE for superior ANC performance with respect to the convergence rate and noise reduction level.

Optimal and Adaptive Virtual Unidirectional Sound Source in Active Noise Control

One of the problems concerned with active noise control is the existence of acoustical feedback between the control value (“active” loudspeaker output) and the reference signal. Various experiments show that such feedback can seriously decrease effects of attenuation or even make the whole ANC system unstable. This paper presents a detailed analysis of one of possible approaches allowing to deal with acoustical feedback, namely, virtual unidirectional sound source. With this method, two loudspeakers are used together with control algorithm assuring that the combined behaviour of the pair makes virtual propagation of sound only in one direction. Two different designs are presented for the application of active noise control in an acoustic duct: analytical (leading to fixed controller) and adaptive. The algorithm effectiveness in simulations and real experiments for both solutions is showed, discussed, and compared.

Adaptive active noise control incorporating with a transfer function method for reducing acoustic feedback in a duct

In most practical applications of active noise control, the acoustic feedback is a major problem that often interferes with the operation of the control system and even renders it unstable. We propose a frequency-domain method based on transfer function to reduce the influence of acoustic feedback based on plane wave transmission theory of sound in a duct. The original signal of primary noise is obtained from the measured signals of reference microphone and error microphone which are transformed to frequency domain by FFT and operated by the proposed method. In this study, Filtered-X LMS algorithm is applied to carry out the active noise controller incorporating with this transfer function method. Experimental results of active noise control show that the system has achieved 18.5 dB maximal attenuation in the frequency band 200-600 Hz. On the contrary, it is only attenuate 3-4 dB if acoustic feedback is present. Therefore, it was to verify that the proposed method of acoustic feedback cancellation incorporating with the Filtered-X LMS algorithm can effectively reduce the influence of acoustic feedback and obtains a better performance of active noise control in a duct.

Phase spectral processing for improved time-domain soft microphone based noise estimation

'Soft Microphones' (SM) constitute a cost-effective, yet quality alternative to the multiple microphones measurement, in applications related to noise mapping. SM offer a solution of great interest to real field applications, e.g., industrial plants. The SM approach, proposed in previous work of the authors, is based on the estimation of the noise signal and the calculation of noise levels over a set of points within the space of interest. To this end, a novel, frequency domain method was introduced and verified in a real field, textile plant experiment, with satisfactory results. However, in order to expand the use of SM from accurate noise mapping to a full Active Noise Control application, it is necessary to obtain accurate noise signal estimates in the time rather than the frequency domain. Further research into the deconvolution step of the proposed method reveals that discontinuities, appearing across the phase spectrum of the estimated signals, cause ambiguities that affect the deconvolution process. We propose here the use of the Hartley transform phase spectrum, which conveys fewer discontinuities as compared to its Fourier Transform counterpart, while it allows for a discontinuities compensation scheme. Experimental results verify that phase spectrum preprocessing provides accurate time domain signal estimates.

Active snore noise control systems

This paper presents an application of active noise control (ANC) algorithms for reducing snoring noise. The snore ANC system installed on a traditional headboard has potential benefits of retrofitting, convenience, and being unobtrusive. ANC algorithms in both single-channel and multiple-channel structures have been developed and tested to evaluate their performance for canceling snore. Adaptive infinite impulse response (IIR) filters and adaptive finite impulse response (FIR) filters with feedback neutralization were examined on their effectiveness of reducing acoustic feedback. Real-time experiments were conducted using a digital signal processor development system and recorded snore samples. An average reduction of 15 to 20 dB at both ears of snorer's bed partner can be achieved using multiple-channel ANC systems.

Fast-Array Adaptive IIR Filter For Active Noise and Vibration Control Systems

In this paper an RLS-based adaptive controller for active noise and vibration control systems is presented. This adaptive controller is designed based on feed-forward architecture and uses IIR filter as the control filter. Because the derived algorithm for ANVC systems is based on RLS recursion, its computational complexity is of order O(n2) which is too high for real-time implementations. Besides, it is also vulnerable to round-off and finite precision errors that may occur in real-time implementation of the algorithm. Since the aim is to test the algorithm in an experimental duct a fast array implementation of the algorithm is proposed. This fast array form is used the extended the fast array algorithms for FIR filter which is studied in literature before. The proposed fast array solution of the algorithm not only reduces the computational complexity to the order of O(n) with the same performance, but also because of its matrix nature it has good numerical stability in real-time applications which is a necessity in active noise and vibration control applications.

Implementation of Single and Multiple Adaptive Step-Size Algorithm to ANC

The purpose of this paper is to investigate a modified adaptive step-size algorithm and implement an active noise control (ANC) system. It is well known that there is a tradeoff between steady state error and convergence rate depending on the step size. This study shows that the new algorithm can track changes in the dynamic characteristics of the ANC system as well as produce a low steady state error. Simulation results are presented to compare the performance of the new algorithm to the basic least mean square (LMS) algorithm. Although there have been several studies of adaptive step-size algorithms, no quantitative analysis has yet been reported for real time active noise control application as far as the authors know. Experimental results are presented for a duct system. The results indicate that the new algorithm provides better performance than the fixed step-size filtered-X least mean square (FXLMS) algorithm.

Finite Element Modeling of Smart Foam for Active Vibration and Noise Control Applications

A new finite element model for elastic porous materials is introduced. The term “elastic” stems from the fact that the motion of the solid phase is encountered for, resulting in the propagation of the acoustic waves in both the solid and fluid phases. A 3-dimentional analysis is essential to fully describe the dynamic behavior and wave types propagating in the porous materials. When using numerical modeling techniques several difficulties arise due to the 3-dimensional nature of the model. Such difficulties are the high computational effort required for accurately modeling the porous material and the difficulty in coupling this material smoothly to any 2-dimensional flexible structure without introducing a coupling matrix. Therefore, a 2-dimensional finite element model for the porous materials is introduced, where it takes advantage of the 1st order shear deformation theory assumptions first introduced by Mindlin for modeling thick plates. Comparing the newly developed 2-dimensional model for partially reticulated polyurethane foam with the original 3-dimentional model based on the 3D elasticity theory has revealed good results when the thickness-to-width ratio doesn't exceed the limits posed by Mindlin for accurate representation of thick plates. The 2-dimensional model was experimentally verified by developing a new type of smart foam, which by attaching to a flexible plate coupled with an acoustic cavity showed good match between the numerical and experimental results.

Optimization of control source locations in an active noise control application of axial cooling fans using genetic algorithms

By placing control sources in the near field, global attenuation of an axial cooling fan’s blade passage frequency and harmonics can be achieved using active noise control. The optimal position of control sources when modeling a fan, whose characteristics differ significantly from a single monopole source or when modeling more than one fan, will be discussed. The number of control sources, as well as position of control sources, are optimized for specific primary source configurations using genetic algorithms. Source strength of control sources are calculated analytically to minimize radiated sound power. The results of optimization using different forms of genetic algorithms will be presented and compared. The results obtained from the genetic algorithms will be compared to experimental results using multiple sources.