Efficient algorithm for active noise control of impulsive noise

Impulsive noise reduction is a special problem raised in active noise control (ANC) systems. The filtered-x least mean square (FxLMS) algorithm is a typical ANC method that has been successfully applied in practical applications. Some variants such as the logarithmic FxLMS and modified FxLMS algorithms have been proposed to deal with the impulsive noise for ANC. However, those methods require considerable computational loading in real-time applications. In this paper, a modified median FxLMS method is proposed for its low complexity to avoid the effect of the impulsive noise. Simulation results show that the proposed algorithm has better averaged noise reduction performance than the conventional FxLMS and other order statistics based FxLMS algorithms. In addition, the computational complexity stays the minimum requirement through using only the ordering operation, which is very suitable for the real-time implementation.

This paper presents an online secondary path modeling method in active noise cancellation based on an enhanced Filtered-X Least Mean Squares (FxLMS) algorithm, implemented on an Altera Cyclone II board. The main specifications of the proposed algorithm are: (1) it avoids overdriving noise in ear by applying a limiter block, (2) it updates online secondary path modeling filter coefficients, utilizes error signal power, and minimizes system error by injecting random white noise at an appropriate time, which can modify the system changes, and (3) it synthesizes the hardware architecture using VHDL Hardware Description language for an Altera Cyclone II board. In this architecture, only 22 of 300 embedded multipliers and 6% of the logical elements in the FxLMS algorithm have been used. The proposed method has used less than 1% of the Field-programmable Gate Arrays’ board memory. The experiments illustrate convincing results in terms of accuracy, convergence speed, and functionality of the designed and implemented system.

The notable advantages of Filtered-x Least Mean Square (FXLMS) Algorithm over other algorithms in Active Noise Control (ANC) environment are its simple time realization, Low computational complexity, robustness and simplicity though the algorithm has slow convergence. In order to optimize its frequency dependent convergence value, a convergence parameter is used. Thus upon application of this algorithm to noise cancellation techniques especially when the noise contains multiple tones, the optimization of the convergence parameter can only be done for one of those tones. The rest of the tones will have a convergence rate slower than the tone for which the convergence parameter is optimized. Again the remaining tones will have less attenuation than they would have if they were to be optimized separately for different tones. In this paper, two more filters are added to the existing structure of the FXLMS algorithm. The concept of Soft Threshold is also introduced in order to achieve better performance in terms of speed of convergence. Furthermore the proposed algorithm is applied to noise cancellation having both Single tone and Multi tone noise and the results are compared with the existing FXLMS and Filtered-X Recursive Least Square algorithm.

Active control of impulsive noise based on a modified convex combination algorithm

Power transformers are known to generate noise, however, active noise emanating from power transformers many at time is unbearable and has been a subject of concern overtime in power engineering. Several studies on it have principally centered on single channel active noise controller (scANC) using fixed step size, which are characterized with the problems such as signal congestion and instability. This study, therefore, employed Filtered-X Least Mean Square (FXLMS) on a dual channel active noise controller (dcANC) using variable step-size. The noise emanating from a 100 MVA, 132/33 kV power transformer was captured with the help of a smart phone in flight mode in accordance with IEC 60076-10 standard of 2 m away from the transformer and 1 m apart between each measurement. The recorded noises were taken at one-third of the height of the transformer tank, while electromagnetic interference from the phone and others were assumed to be negligible. A dcANC with FXLMS was model mathematically and implemented in Simulink in the MATLAB environment. Noise reduction ratio, loudness unit full scale and mean square error were used as performance metrics. The simulation results obtained showed that the original noise emanating from the power transformer when ANC was not used was found to be 70 dB. When scANC with FXLMS was used, the noise was reduced to 30.55 dB whereas, when dcANC with the FXLMS was employed it was reduced to 0.19 dB. Also, the MSE value of -72 dB was obtained in the proposed dcANC with FXLMS, compared with -64 dB obtained from scANC with FXLMS algorithm. The results of the simulation using FXLMS on both scANC and dcANC showed that the performance of the dcANC is comparatively better in term of the stated performance metrics.

Active control for vehicle interior noise based on DWT-FxLMS algorithm using a piezoelectric feedback system

Filtered-x generalized mixed norm (FXGMN) algorithm for active noise control

All-pass filtered x least mean square algorithm for narrowband active noise control

Filtered-X least mean square (FXLMS) algorithm is widely used in active noise control (ANC) systems when the secondary path is linear. However, the performance of FXLMS reduces when nonlinearity is present. Leaky FXLMS (LFXLMS) and minimum output variance FXLMS (MOVFXLMS) algorithms are effective in compensating the nonlinearity effects in nonlinear ANC (NANC). When using optimum leakage factors, these algorithms show close performance with benchmark nonlinear FXLMS (NLFXLMS) algorithm. In all three algorithms, the degree of nonlinearity must be known in advance and are usually assumed. In previous works, Tangential Hyperbolic Function NLFXLMS (THF-NLFXLMS) algorithm has been developed whereby the degree of nonlinearity is estimated using tangential hyperbolic function (THF). In this work, the performance of LFXLMS and MOVFXLMS based on optimum leakage factors calculated using the estimated degree of nonlinearity is compared with THF-NLFXLMS for Hammerstein structure. The results show that optimum MOVFXLMS performs similarly to optimum LFXLMS and THF-NLFXLMS.

The noise in the marine engine room has always been a major cause of disturbance and damage to sailors’ physical and mental health; however, the antinoise countermeasures were being ignored by the industry. To further reduce the noise in the marine engine room, the system structure of active noise control (ANC) and the theoretical basis of the least mean square (LMS) and filtered X least mean square (FXLMS) algorithm are studied. Based on the FXLMS algorithm ANC system, the simulation study of active noise control in the marine engine room of a multigas carrier is carried out. According to the simulation results by the diagrams plotted on the time domain and spectrum, the ANC systems with the FXLMS algorithm can effectively reduce the noise in the marine engine room by about 20 dB, especially for the peak low-frequency range of 20–500 Hz with a large antinoise effect.

A robust evolutionary feedforward active noise control system using Wilcoxon norm and particle swarm optimization algorithm

This papers aims to develop an Adaptive Feedback Active Noise Control (AFB-ANC) system comprising two adaptive filters. The first adaptive filter is the same as found in the traditional AFB-ANC systems and is adapted using the classical Filtered-x Least Mean Square (FxLMS) algorithm. The stability of the FxLMS algorithm requires filtering the reference signal via a `good' estimate of the cancellation path (CP) present between the cancellation loudspeaker and the error microphone. Since the CP may be time-varying in the practical situations, the task of the second adaptive filter is to provide estimation of the CP during operation of the AFB-ANC system. The Cancellation-Path Estimation (CPE) filter is excited by a probe signal and is adapted using a delay-based Normalized Least Mean Square (NLMS) algorithm. The proposed system is equipped with a simple strategy to monitor the convergence status of the CPE filter. The developed strategy allows to inject a large (small) probe signal during the transient (steady) state of the AFB-ANC system. Computer simulation are carried out which demonstrate the effective performance of the developed system.

To clarify the performance differences and applicable scenarios of three adaptive filtering algorithms, namely FxLMS (Filtered-X Least Mean Square), FxRLS (Filtered-X Recursive Least Squares), and FxNLMS (Filtered-X Normalized Least Mean Square), this study conducts a comparative investigation from the perspectives of principle, performance, and application. Firstly, the core logic of each algorithm is analyzed in depth: FxLMS is based on the least mean square criterion, adjusting weights through secondary path filtering, which features low computational complexity but relatively slow convergence; FxRLS relies on the recursive least squares criterion, achieving fast convergence via recursive weight updating while suffering from high computational load and sensitivity to initial values; FxNLMS integrates a normalized step size design, balancing convergence speed and stability with stronger adaptability to variations in signal power. Subsequently, key performances of the three algorithms are compared through simulation experiments: FxRLS exhibits the optimal convergence speed, followed by FxNLMS, with FxLMS being the slowest; in terms of steady-state error, FxRLS and FxNLMS demonstrate superior performance, whereas FxLMS is significantly affected by model accuracy; the computational complexity follows the order of FxRLS>FxNLMS>FxLMS. Finally, combined with application scenarios such as active noise control and communication signal processing, specific suggestions for algorithm selection under different requirements are proposed.

In this paper we consider active noise control (ANC) of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems is based on second order moment of error signal, and hence, becomes unstable for the impulsive noise. Recently we have proposed variants of the FxLMS algorithm where improved performance has been realized either by thresholding the input data or efficiently normalizing the step-size for adaptation. In the practical ANC systems, these thresholding parameters need to be estimated offline and cannot be updated during online operation of ANC systems. Furthermore, normalizing the steps-size for an impulsive noise source would essentially freeze the adaptation for very large impulses. In order to solve these problems, in this paper we propose a novel approach for ANC of impulsive noise sources. The proposed approach is based on data-reusing (DR) type adaptive algorithm. The main idea is to improve the stability by normalizing the step-size, and improve the convergence speed by reusing the data. The computer simulations are carried out to verify the effectiveness of the proposed algorithm.

The paper presents a study on adaptive vibration control applied in a semi-active vehicle suspension. The simulation-based analysis is dedicated to laboratory tests conducted for an experimental all-terrain vehicle subjected to mechanical exciters emulating road-induced vibration. The implemented simulation environment consists of a full-car model which exhibits seven degrees of freedom (7 DoFs), equipped with magnetorheological dampers. The MR damper model based on hyperbolic tangent function was included in the vehicle model. The front wheels of the model were subjected to sinusoidal excitation with constant frequency within the range 0.5–25 Hz. The FxLMS (Filtered-x Least Mean Squares) algorithm is adopted and used for controlling the MR dampers where the vertical velocity of excitation is assumed as a reference signal of the control algorithm. The goal of the algorithm is to attenuate vertical velocity of the front middle vehicle body part. The proposed FxLMS was compared to passive suspension controlled with constant control current and Skyhook algorithm. Comparison of different suspension configurations based on transmissibility characteristics and quality indices confirm usefulness of FxLMS with respect to vibration control, suspension deflection and adaptability features.