Online Secondary Path Modeling Research Articles

Multi-channel ANC System with Online Secondary Path Modeling for Turboprop Aircraft Cabin

Multi-channel ANC System with Online Secondary Path Modeling for Turboprop Aircraft Cabin

Simultaneous perturbation algorithm for active noise control with an asynchronous wireless microphone

This paper investigates the issues on the use of an asynchronous wireless microphone in an active noise control (ANC) system. In a previous work, the jitter effect of the wireless error microphone is addressed by adopting the simultaneous variable perturbation (SVP) algorithm to update the control filter of the ANC system. However, another critical issue has been overlooked. The wireless microphone can have a different sampling rate from that of the ANC controller, because the analog-to-digital convertors for the ANC controller and the wireless microphone are triggered by separate crystal oscillators. This may deteriorate the convergence performance of the ANC system. In this paper, the simulation results demonstrate that both the SVP and online secondary path modeling (OSPM) algorithms are not affected by the sampling rate of the wireless error microphone, when the sampling rate difference is less than 0.01%. However, the sampling rate difference of the wireless reference microphone can lead to about 7 dB and 5 dB degradations in the noise reduction performance of the SVP and OSPM algorithms, respectively.

Frequency domain online secondary path modelling for active noise control without auxiliary noise

The identification of the secondary path transfer function is of vital importance for active noise control (ANC) system. Online secondary path modeling method is preferable to offline modeling due to its tracking capability in time-varying acoustic environments. However, the auxiliary noise of online modeling mixed with the residual error signal diminishes the noise control performance. In this paper, we propose a frequency domain online secondary path modelling algorithm based on our previous work which achieves simultaneous acoustic paths modeling and noise control without auxiliary noise. The uniqueness of the solution is theoretically analyzed, and the computational burden is shown significantly lower than the previously proposed method. Simulations are conducted to verify that the proposed algorithm also has a better convergence behavior.

A Computation-efficient Online Secondary Path Modeling Technique for Modified FXLMS Algorithm

This paper proposes an online secondary path modelling (SPM) technique to improve the performance of the modified filtered reference Least Mean Square (FXLMS) algorithm. It can effectively respond to a time-varying secondary path, which refers to the path from a secondary source to an error sensor. Unlike traditional methods, the proposed approach switches modes between adaptive ANC and online SPM, eliminating the use of destabilizing components such as auxiliary white noise or additional filters, which can negatively impact the complexity, stability, and noise reduction performance of the ANC system. The system operates in adaptive ANC mode until divergence is detected due to secondary path changes. At this moment, it switches to SPM mode until the path is remodeled and then returns to ANC mode. Furthermore, numerical simulations in the paper demonstrate that the proposed online technique effectively copes with the secondary path variations.

Convex combination of online secondary path modeling and improved cuckoo search for active noise control

This paper proposes an active noise control (ANC) algorithm based on convex combination of the online secondary path modeling (OSPM) and improved cuckoo search (ICS) algorithms. The ICS algorithm does not request the secondary path model to optimize the control filter. Therefore, the ICS algorithm is theoretically not affected by a varying secondary path, but its convergence is very slow. In contrast, the OSPM algorithm achieves faster convergence but is vulnerable to a sudden change in the secondary path. The proposed ANC algorithm combines the merits of both the OSPM and ICS algorithms by convex combination. Simulation results show that the proposed ANC algorithm can achieve better performance than the conventional ANC algorithm especially when the secondary path changes drastically.

A robust auxiliary noise power scheduling strategy for online secondary path modeling in active noise control systems

Auxiliary noise injected in active noise control (ANC) systems for online secondary path modeling (SPM) contributes to the residual noise, and thus deteriorates the noise control performance of ANC systems. Moreover, sudden changes in secondary path may lead to easy divergence of the existing online SPM methods. This paper improves the existing methods from three aspects to further mitigate these problems: 1) the noise power is varied on the basis of the convergence status of SPM filter so that large-power noise is injected at the start or when secondary path changes and the power is reduced as the filter converges. 2) a novel ON/OFF controlling strategy is used in the method so that the noise injection is suspended at the optimum point when the modeling accuracy is sufficient. 3) continuous check for error outliers is applied in the method to detect changes in secondary path so that the injection of noise can be reactivated in the case of path perturbation. Comparative simulations show the effectiveness of the improved method both in convergence and noise reduction performance. In addition, the improved method is robust against sudden changes in secondary path.

A robust feedforward hybrid active noise control system with online secondary‐path modelling

In this study, a robust feedforward hybrid active noise control (ANC) system with online secondary-path modelling (SPM) is proposed that is capable of not only effectively suppressing the broadband and narrowband noise components but also tracking the secondary path (SP) variations. An finite impulse response online SPM subsystem as well as an efficient decoupling filter are included in the proposed feedforward hybrid ANC (HANC) system. The decoupling filter is a parallel-form bandpass filter bank that consists of multiple bandpass filters that are derived from the second-order infinite impulse response notch filters. It takes the residual noise as its input and separates the broadband component from the narrowband component, with the former used as not only a desired signal for the SPM but also as an error signal for updating the broadband sub-controller, whereas the latter adapted simultaneously to scale the auxiliary white Gaussian noise and to update the narrowband sub-controller. Extensive simulations are conducted with both the synthetic and real SPs as well as the synthetic and real noise signals that are generated by a large-scale factory cutting machine (strand-cutter) to demonstrate the advantages and effectiveness of the proposed feedforward HANC system. Comparisons are also demonstrated with the original HANC system as well as its directly extended version with an online SPM subsystem.

Careful least squares active noise control with no prior secondary path model

SummaryIn feedforward active noise and vibration control (ANVC) or active noise control (ANC), with online secondary path modeling, fast converging overall modeling algorithms may give high modeling errors. These errors are due to the highly correlated inputs, namely the reference and antinoise signals. These high modeling errors can result in poor performance if ignored. However, it is possible to consider these modeling errors in the control filter design, resulting in a careful controller and good performance, as proposed in this work. Careful control is a dual controller feature, which is the solution to the optimal control problem, but this has not been proposed before in the context of ANC. The modeling error covariance matrix (Sigma(n)) is available in the Kalman filter. However, this requires the knowledge of the time‐varying measurement noise power q(n) and state noise. Instead, this work uses a different approach in which the corresponding linear system is solved in a non‐recursive manner. The resulting maximum error is used for a worst‐case estimate of q(n), and, as it turns out, this can be used to get a worst‐case estimate of Sigma(n). A lower control filter update frequency and other optimizations keep computational complexity similar to other approaches. The resulting algorithm has very few easily selected parameters, good performance, does not require any prior secondary path estimate, and adapts to slow and sudden changes in the physical paths without loss of performance or noise overshoots. However, performance can be impaired by large background noise levels.

An improved parallel narrowband active noise control system with local on-line secondary-path modeling equipped with frequency estimation algorithm

Active noise control technology shows good performance in those low-frequency narrowband noise control applications. Suffering from time-varying frequencies and secondary path, the performance of narrowband active noise control system may deteriorate seriously. In this work, an improved narrowband active noise control system is proposed to improve the noise reduction performance in those time-varying system. In the improved system, a frequency tracker based on the adaptive notch filter is adopted to estimate the frequencies of the noise signal. The result of frequency estimation is used to generate the reference signal and the prior information of the secondary-path modeling process. Then, the local secondary-path modeling can be conducted in the system with unknown fixed tonal noise signal or time-varying tones. Simulations and experiments are conducted to verify the performance of the proposed algorithm, and the results show that the proposed algorithm has good behavior.

A Robust Feedback Active Noise Control System With Online Secondary-Path Modeling

In this letter, a robust feedback active noise control (FBANC) system with an online secondary-path modeling (OSPM) subsystem is proposed for suppressing sinusoidal noise signals. First, a decoupling scheme is proposed by using of an adaptive linear prediction filter (LPF) that takes the FBANC residual noise as its input and separates the remaining sinusoidal noise from the broadband noise that includes an inherent additive noise within the primary noise as well as a broadband component due to an auxiliary white Gaussian noise (AWGN). The remaining sinusoidal noise (LPF output) is used effectively not only to update the FIR controller but also to scale the AWGN, while the broadband noise (LPF error) serves as a desired signal for the OSPM. In this way, the hostile coupling between the FIR controller and the OSPM subsystem is significantly mitigated, leading to both faster system convergence and improved noise reduction performance (NRP). Second, a simple and practical scheme for refreshing the proposed FBANC system is also developed to enhance its robustness against even abrupt changes with the SP and/or the primary noise signal. Extensive simulations with synthetic and real secondary paths and noise signals are conducted to demonstrate the effectiveness of the proposed FBANC system.

A new online secondary path modeling method with white noise amplitude adjustment for excavator cab

This article describes a new active noise control system to reduce the noise in the excavator cab. The noise in the excavator cab is mainly low-frequency noise. A digital signal processor (DSP) is selected to control the microphone and speaker for active noise control. In the traditional online secondary path modeling method, the amplitude of the white noise is fixed, and the amplitude of the white noise is still large after the modeling is completed, which will affect the reference microphone. In response to the above problems, I made improvements in the traditional algorithm and added a white noise amplitude adjustment module. After the iterative algorithm of the identification filter converges, the amplitude of the white noise is reduced. In addition, when the secondary path is disturbed, the amplitude of the white noise is increased in order to remodel the secondary path. That is to say, the white noise amplitude adjustment is based on the first-order forward difference of the square value of the error signal every 50 times. What’s more, the iterative algorithm of the control filter and the identification filter adopts the idea of variable step size, which can speed up the convergence of the algorithm. Finally, the feasibility of the algorithm is verified through matlab simulation and experiment. In the simulation, it can achieve a noise reduction of about 11dB. In the experiment, a noise reduction of 5dB can be achieved, and a noise reduction of 9dB can be achieved at the frequency with the largest noise amplitude. In a word, the proposed algorithm is superior to traditional online secondary path modeling algorithm.

A Noise Control Method Using Adaptive Adjustable Parametric Array Loudspeaker to Eliminate Environmental Noise in Real Time.

Long-term exposure to environmental noise is dangerous to human health. Therefore, there is an urgent need to suppress or eliminate environmental noise. Due to the limitation of environmental space, the use of reverse sound waves emitted by loudspeakers for noise elimination has been widely used in noise control. However, because of the omni-directionality of sound propagation, a traditional voice coil loudspeaker (VCL) is used as a secondary source (emission reverse sound wave). It is easy to increase the sound pressure in non-target areas and form significant acoustic feedback to the reference source. Therefore, we propose an online secondary path modeling method using an adjustable parametric array loudspeaker (PAL) based on ultrasounds to eliminate environmental noise in real time. According to the different distance of the target, the size of the PAL is adjusted adaptively to realize the noise control of different long-distance targets. The distribution of quiet areas is discussed. The experimental results showed that a PAL as a secondary source had the same noise reduction effect as a traditional VCL, but it had longer propagation distance, smaller sound feedback and a more regular and controllable distribution of quiet areas. These research findings have great potential for improving environmental noise and creating a quiet environment.

An efficient narrowband active sound profiling system with online secondary path modeling

Active noise equalization or active sound profiling techniques for sound quality enhancement tend to balance the sound pressure levels (SPLs) of certain frequency points or frequency bands of target noise to meet human perception requirements rather than simply minimizing the SPLs like active noise control (ANC) technique. Therefore, when the secondary path is time-varying, online secondary path modeling (OSPM) appears particularly important in the active sound quality enhancement systems. This paper presents a novel parallel-structure narrowband active sound profiling (NASP) system with OSPM. In the system, the OSPM subsystem uses the control signals to estimate low-order local secondary path models at the controlled frequencies instead of the usual high-order global model. This way may ensure the convergence speed and accuracy of modeling. Meanwhile, the main sound profiling subsystem employs the estimated local secondary path models to profile the targeted multi-tonal narrowband noise based on the internal model FXLMS algorithm. By using bandpass filter banks, each tonal component may be tuned relatively independently. In addition, the proposed system enjoys good profiling accuracy and stability since no additional random noise is introduced. Several simulations are provided to demonstrate the superiority of the proposed NASP system with OSPM in cancellation mode over the conventional NANC system with OSPM and evaluate the behavior of the proposed system in different time-varying scenarios. Finally, real-time experiments are also conducted to confirm the system’s ability to deal with sudden changes in the secondary path and its sound profiling capability.

Frequency domain analysis of the mirror‐modified filtered‐x least mean squares algorithm with low ambient noise

SummaryThe mirror‐modified filtered‐x least mean squares (MMFxLMS ) algorithm is a variation of the FxLMS algorithm with online secondary path modeling that cannot diverge due to secondary path modeling errors. However, problems may occur when the ambient noise is not limited due to insufficient modeling power. This work shows that under a frequency domain analysis without ambient noise, the MMFxLMS algorithm is always stable, and expressions for the maximum residual noise level at any given time are obtained. It is also shown that, under the same context, convergence to the minimum residual noise is guaranteed. Still, convergence can be much slower for high secondary path modeling errors than that of the LMS or MFxLMS algorithms. Simulations confirm these results.

FxRLS Algorithms Based Active Control of Impulsive Noise With Online Secondary Path Modeling

Active noise control algorithms undergo stability problems in the presence of impulsive noise. This paper investigates such algorithms with online secondary path modeling for impulsive noise and varying acoustic paths. The paper presents three methods for active noise control, along with improved online secondary path modeling. Firstly, the filtered x recursive least square algorithm is applied for both active noise control and online secondary path modeling. This method gave faster convergence, improved stability, and modeling accuracy as compared to existing ones. The filtered x recursive least square algorithm is not robust for abruptly changing acoustic paths. To overcome this problem another method that uses modified gain filtered x recursive least square algorithm for active noise control is presented. Furthermore, it is observed that modified gain filtered x recursive least square achieves the desired performance with overheads of increased complexity. Thus, a hybrid method is proposed which has less computational complexity than the rest methods with no compromise on active noise control system performance.

Spatial Active Noise Control in Rooms Using Higher Order Sources

All spatial active noise control (ANC) systems, when deployed in typical room environments, have time-varying acoustic channels between the secondary sources and the error microphones. The conventional online secondary path modeling techniques, which introduces additive auxiliary random noise to estimate the secondary paths, become challenging especially in a multichannel setup. In this work, we propose to use higher-order variable-directivity sound sources as secondary sources for spatial ANC, in which both the interior residual noise field within the control region and exterior sound field due to secondary source radiation are jointly controlled. The aim of controlling the exterior sound field is to minimize room reverberation generated by the secondary sources so that the secondary paths in the proposed algorithm can be approximated as free-field propagation and thus can be pre-calibrated. The system is implemented in an adaptive manner to track noise variations. The results show that the proposed method can effectively cancel spatial noise field and control exterior sound field at an acceptable low level in time-varying room environments.

Analysis of Techniques for On-Line Secondary Path Modeling in ANC Systems

The on-line secondary path modeling of an ANC systems is the most relevant issue. Currently there are algorithms to obtain fast convergence, adequate stability and minimum error. In this article, the properties of these algorithms are analyzed, as well as the architectures for their possible implementation in hardware. The performance comparison is carried out with behavioral simulation, and its suitability for active noise cancellation is evaluated. Based on the results of the analysis, a new algorithm is proposed, suitable for its implementation in hardware. The results obtained present an attenuation of the order of -31dB, which is the highest attenuation reported so far

Design of Variable Auxiliary Noise Influence Ratio for Adaptive Active Vibration Control

Active vibration control (AVC) is an effective way to reduce low-frequency vibration. Accurate secondary path modeling (SPM) is crucial for the implementation of AVC system based on filtered-x least mean square (FXLMS) algorithm. The FXLMS algorithm with online SPM comprises two filters, i.e., an active control filter and an online SPM filter. Mutual interference between them is the key factor that restricts the performance of AVC system with online SPM. This paper designs a novel approach based on variable auxiliary noise influence (ANI) ratio to measure the contrastive relationship of convergence status between the active control filter and the online SPM filter. Based on the proposed variable ANI ratio, the proportion of auxiliary noise component in residual vibration is scheduled. Furthermore, a variable step-size strategy is derived to realize fast and stable online SPM. Comparative simulations with the competing methods are carried out in the case of secondary path sudden change and broadband vibration control. The simulation results indicate that the proposed method gives better performance than the other competing methods.

Auxiliary-Noise Power-Scheduling Method for Online Secondary Path Modeling in Pre-Inverse Active Noise Control System

Auxiliary-Noise Power-Scheduling Method for Online Secondary Path Modeling in Pre-Inverse Active Noise Control System

A 5-stage active control method with online secondary path modelling using decorrelated control signal

Time-varying primary and secondary paths in active control systems degrade the noise control performance. In this paper, a practical method is proposed for active control systems with online secondary path modelling using the decorrelated control signal. The proposed method consists of 5 stages, i.e., primary path estimation, controller initialization, secondary path estimation, primary and secondary path changing detection, and active control operation, where the speed of the secondary path modelling is improved by incorporating decorrelation filters. The simulation results demonstrate the proposed method is capable of tracking the changes in both primary and secondary paths, remodelling the secondary path, and maintaining the noise reduction performance and stability of the system when both primary and secondary paths change.