A model is extremely important to the controller designing and system analysis of an active vibration control system. However, the influence of actuators is always ignored by considering them as proportion links when ...
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A model is extremely important to the controller designing and system analysis of an active vibration control system. However, the influence of actuators is always ignored by considering them as proportion links when modeling the control system. In this work, a joint model of a clamped-free shell structure and electrodynamic actuators was constructed. The shell was modeled using the finite element method while the actuators were simplified as lumped parameter models. It was found that the connections of actuators diminish the natural frequencies and smooth the resonance peaks of the structure. The optimal configuration of actuators and sensors was studied by harmonic response analysis and modal analysis. It was suggested to avoid the central line and give priority to the free end or the edges of the clamped-free shell when mounting actuators and sensors. The active control was carried out using the fxlms algorithm, which effectively suppressed the disturbance of the vibration source. The control was conducted point by point on the transient response model of the structure and can easily be extended to a real life system.
Active noise control (ANC) technique has been successfully implemented by various automotive manufacturers to interior powertrain noise cancellation and/or sound management. For the powertrain noise control, the ANC s...
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ISBN:
(数字)9783319299563
ISBN:
(纸本)9783319299563;9783319299556
Active noise control (ANC) technique has been successfully implemented by various automotive manufacturers to interior powertrain noise cancellation and/or sound management. For the powertrain noise control, the ANC system only requires one reference signal (typically using tachometer signal) due to the fact that the powertrain response is functionally related to the engine rotational speed. Instead, the multi-reference ANC system is often required for the road noise control since the multiple-coherence between the reference accelerometer signals and the target noise must be guaranteed to yield an acceptable control performance. However, the adoption of traditional multi-reference filtered-x least mean square (fxlms) algorithm for road noise ANC often leads to a large computational burden and slow convergence rate due to the long length of adaptive filter and a huge dynamic range of the filtered reference signal. To address these problems, road noise ANC systems configured with the time-frequency domain fxlms (TF-fxlms) algorithm and subband fxlms (Sfxlms) algorithm are developed, where the adaptive algorithm either calculates the gradient estimate and filtered reference signal in the frequency domain or subband frequency domain to reduce the computational requirement and also updates the control signals in the time domain to avoid delay in the reference path. Then, a comprehensive computational complexity analysis is conducted to exhibit the computational cost for different algorithms. The effectiveness of the different algorithms will be demonstrated through an ANC system with eight accelerometers, one secondary loudspeaker, and one error microphone in the driver side to control actual road noise.
Noise is unavoidable in a vibration control system due to the complexity of the actual application environment and the measuring limitation of sensing devices. In this paper, the jamming effects on the convergence pro...
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ISBN:
(纸本)9781467399784
Noise is unavoidable in a vibration control system due to the complexity of the actual application environment and the measuring limitation of sensing devices. In this paper, the jamming effects on the convergence process is analyzed and then we propose a new variable-step adaptive fxlms algorithm which can reduce the negative effects of interference. The new algorithm can not only solve the problem in active vibration control (AVC) properly, but also decrease the misadjustment without slowing down the convergence rate. Simulation and experimental results show that the improved algorithm can effectively reduce the noise interference, and improve the application level of fxlms algorithms in the case of vibration control.
This paper presents the performance of applying the filtered-x least mean squares (fxlms) algorithm to attenuate repetitive impact acoustic noise. The fxlms algorithm has been widely adopted in active noise control (A...
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This paper presents the performance of applying the filtered-x least mean squares (fxlms) algorithm to attenuate repetitive impact acoustic noise. The fxlms algorithm has been widely adopted in active noise control (ANC) system for various relatively stationary disturbances. However, its convergence behavior for transient impulse has not received as much attention. Directly applying this algorithm to individual transient event exhibit difficulties since it requires certain adaptation time to converge satisfactorily. But for transient noise with certain repeatability, the fxlms algorithm may be capable of learning. A theoretical convergence analysis of the fxlms algorithm for repetitive impact noise is conducted. To simplify the derivation, the secondary path is assumed to be a pure delay model. Through this analysis, a step size bound condition is derived, and an optimal step size that leads to the fastest convergence rate is determined. Then, numerical simulations are performed considering various pure delay secondary path models to validate the theoretical analysis. Furthermore, a laboratory test is developed to demonstrate the capability of ExLMS algorithm for active control of repetitive impact noise. The analysis shows promising results of applying active noise control system with the fxlms algorithm to repetitive transient noise typically seen in industrial facilities. (C) 2014 Elsevier Ltd. All rights reserved.
Powertrain noise is a major component of vehicle interior noise and thus has a significant effect on the overall sound quality. It is typically dominated by harmonics in the lower audible frequency range, which are di...
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Powertrain noise is a major component of vehicle interior noise and thus has a significant effect on the overall sound quality. It is typically dominated by harmonics in the lower audible frequency range, which are directly related to the engine firing orders. In order to achieve a more comfortable environment and pleasing driving experience, an active noise control (ANC) applying advanced filtered-x least mean squares (fxlms) algorithm is employed to reduce the vehicle interior noise by targeting these harmonics. The proposed ANC system is designed to control multiple orders of the engine noise response simultaneously. It is also uniquely formulated with a twin-fxlms algorithm to prevent harmonic interference that often resulted in overshoot at some adjacent orders, especially at low engine speed range where the reference sinusoids are close together. In fact, the interference issue is one of the critical problems that previously plagued the use of the conventional fxlms algorithm. The basic design of the twin-fxlms algorithm splits the adaptive filter into two sets. This allows different sum of reference sinusoids to be fed into each adaptive filter in order to widen the frequency separation between two adjacent harmonics. Finally, the performances of proposed twin-fxlms are validated by numerical simulations. [DOI:10.1115/1.4003386]
The popular filtered-x least-mean squares (fxlms) algorithm has been widely adopted in active noise control (ANC) for relatively stationary disturbances. The convergence behavior of the fxlms algorithm has been well u...
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The popular filtered-x least-mean squares (fxlms) algorithm has been widely adopted in active noise control (ANC) for relatively stationary disturbances. The convergence behavior of the fxlms algorithm has been well understood in the adaptation process for stationary sinusoidal or stochastic white noises. Its behavior for transient impulses has not received as much attention. This paper employs the root locus theory to develop a graphical tool for the analysis and design of the adaptive ANC system for repetitive impulses. It is found that there is a dominant pole controlling the stability of the adaptation process, in which the maximum step size can be determined. The analysis also observes a transient adaptation behavior in the fxlms algorithm for repetitive impulses. In this case, the predicted step-size bound decreases as the number of repetitive impulses increases for a general secondary path. Furthermore, the dominant root tuning process is applied by incorporating a digital filter after the output of the adaptive controller, which significantly increases the step-size bound. The accuracy of the analysis was extensively validated by numerical simulation studies by assuming various secondary path models. The simulated results show an excellent agreement with analytical predictions.
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 a...
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ISBN:
(纸本)9789881476807
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 FILMS and modified FILMS 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 deals with the adaptive algorithms for active noise control (ANC) systems being employed for the impulsive noise sources. The standard filtered-x least mean square (fxlms) algorithm;based on the minimizatio...
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This paper deals with the adaptive algorithms for active noise control (ANC) systems being employed for the impulsive noise sources. The standard filtered-x least mean square (fxlms) algorithm;based on the minimization of the variance of the error signal;is well suited for attenuation of Gaussian noise sources. For the impulsive noise;modeled as a stable non-Gaussian process;however, the second order moments do not exist and hence the fxlms algorithm becomes unstable. The filtered-x least mean p-power (FxLMP) algorithm - based on minimizing the fractional lower order moment (FLOM) - gives robust performance for impulsive ANC;however, its convergence speed is very slow. This paper proposes two data-reusing (DR)-based adaptive algorithms for impulsive ANC. The Proposed-I DR algorithm is based on the normalized step-size fxlms (NSS-fxlms) algorithm, and the Proposed-II DR algorithm is based on the Author's recently proposed NSS generalized FxLMP (NSS-GFxLMP) algorithm. Extensive simulations are carried out, which demonstrate the effectiveness of the proposed algorithms in comparison with. the existing algorithms. (C) 2015 Elsevier Ltd. All rights reserved.
The common active noise control (ANC) algorithm, namely the filtered-x least mean square (fxlms) algorithm, becomes unstable for the non-Gaussian impulsive noise. This is because the typical fxlms algorithm is based o...
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The common active noise control (ANC) algorithm, namely the filtered-x least mean square (fxlms) algorithm, becomes unstable for the non-Gaussian impulsive noise. This is because the typical fxlms algorithm is based on the minimization of variance of the error signal (the second order moment in L-2 space), which does not exist for the non-Gaussian impulsive noise. In this study, a family of threshold based algorithms is proposed by minimizing several robust objective error functions as well as thresholding the reference signal to further refine the robustness of the ANC system for impulsive noise. The proposed algorithms are also expected to generalize the existing adaptive algorithms for impulsive noise control. These robust error functions are typically represented by (1) robust space vectors: L-p and Log space;and (2) re-descending M-estimators: Huber, Fair and Hampel threshold functions. The threshold parameters in the reference signal and those M-estimators can be determined by using online and/or offline statistical estimation approaches. Numerical simulations are carried out to verify the performance of proposed algorithms by using synthesized impulsive noise following symmetric alpha-stable (S alpha S) distribution. Results show the improved robustness and convergence performance of the proposed algorithms for ANC of impulsive noises as compared to the conventional algorithms. (C) 2015 Elsevier Ltd. All rights reserved.
Active noise control (ANC) system based on adaptive algorithm is an effective technique for acoustic noise reduction. fxlms is a fairly robust algorithm but it gives inferior performance when secondary path is time va...
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ISBN:
(纸本)9781479984367
Active noise control (ANC) system based on adaptive algorithm is an effective technique for acoustic noise reduction. fxlms is a fairly robust algorithm but it gives inferior performance when secondary path is time varying, as a result, online secondary path modeling has been used. A variable step-size least mean square (VSS-LMS) algorithm with noise power scheduling is implemented in this paper to minimize the noise level. Computer simulations are done in MATLAB and substantial noise reduction in ambulance siren is obtained. The algorithm is implemented to reduce ambulance siren noise causes deterioration in the health of patient lying inside. The result shows that Active noise control (ANC) system using VSS-LMS with noise power scheduling reduces ambulance siren noise considerably by 49 dB.
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