scholarly journals Sequentially Adapted Parallel Feedforward Active Noise Control of Noisy Sinusoidal Signals

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
Govind Kannan ◽  
Issa M. S. Panahi ◽  
Richard W. Briggs
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Random Noise ◽  
Active Noise Control ◽  
Superior Performance ◽  
Filter Method ◽  
Periodic Signal ◽  
Noise Component ◽  
Periodic Noise ◽  
Active Noise

A large class of acoustic noise sources has an underlying periodic process that generates a periodic noise component, and thus their acoustic noise can in general be modeled as the sum of a periodic signal and a randomly fluctuating signal (usually a broadband background noise). Active control of periodic noise (i.e., for a mixture of sinusoids) is more effective than that of random noise. For mixtures of sinusoids in a background broadband random noise, conventional FXLMS-based single filter method does not reach the maximum achievable Noise Attenuation Level (NALmax⁡). In this paper, an alternative approach is taken and the idea of a parallel active noise control (ANC) architecture for cancelling mixtures of periodic and random signals is presented. The proposed ANC system separates the noise into periodic and random components and generates corresponding antinoises via separate noise cancelling filters, and tends to reach NALmax⁡ consistently. The derivation of NALmax⁡ is presented. Both the separation and noise cancellation are based on adaptive filtering. Experimental results verify the analytical development by showing superior performance of the proposed method, over the single-filter approach, for several cases of sinusoids in white noise.

scholarly journals Multichannel Feedforward Active Noise Control System with Optimal Reference Microphone SelectorBased on Time Difference of Arrival

2018 ◽  
Vol 8 (11) ◽  
pp. 2291 ◽  
Author(s):  
Kenta Iwai ◽  
Satoru Hase ◽  
Yoshinobu Kajikawa
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Control Point ◽  
Active Noise Control ◽  
Broadband Noise ◽  
Time Difference ◽  
Arrival Direction ◽  
Noise Sources ◽  
Time Difference Of Arrival ◽  
Active Noise

In this paper, we propose a multichannel active noise control (ANC) system with an optimal reference microphone selector based on the time difference of arrival (TDOA). A multichannel feedforward ANC system using upstream reference signals can reduce various noises such as broadband noise by arranging reference microphones close to noise sources. However, the noise reduction performance of an ANC system degrades when the noise environment changes, such as the arrival direction. This is because some reference microphones do not satisfy the causality constraint that the unwanted noise propagates to the control point faster than the anti-noise used to cancel the unwanted noise. To solve this problem, we propose a multichannel ANC system with an optimal reference microphone selector. This selector chooses the reference microphones that satisfy the causality constraint based on the TDOA. Some experimental results demonstrate that the proposed system can choose the optimal reference microphones and effectively reduce unwanted acoustic noise.

scholarly journals ACTIVE NOISE CONTROL USING NEURAL SYSTEM

2010 ◽  
Vol 13 (3) ◽  
pp. 67-74
Author(s):  
Tuan Van Huynh ◽  
Nghĩa Hoai Duong
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Active Noise Control ◽  
Neural System ◽  
Control Area ◽  
New Method ◽  
Traditional Methods ◽  
Active Noise ◽  
Opposite Phase ◽  
Simulation Results

The principle of active noise control (ANC) is to produce a secondary acoustic noise which has the same magnitude as the unwanted primary noise but with opposite phase. The sum of these two signals reduces acoustic noise in the noise control area. In this paper we present a new ANC method using neural system. Moreover a new method for compensating the saturation of the power applifier is also introduced. The performance of the proposed method is compared to that of traditional methods. Simulation results are provided for illustration.

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

2021 ◽  
Vol 312 ◽  
pp. 08007
Author(s):  
Marco Ciampolini ◽  
Lorenzo Bosi ◽  
Luca Romani ◽  
Andrea Toniutti ◽  
Matteo Giglioli ◽  
...  
Keyword(s):  
Acoustic Waves ◽  
Noise Control ◽  
Noise Source ◽  
Acoustic Noise ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Destructive Interference ◽  
Exhaust Pipe ◽  
Least Mean Square ◽  
Active Noise

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.

Nonlinear active noise control using adaptive rational functions with second-order poles frames: Simulation and experimental results

2014 ◽  
Vol 229 (9) ◽  
pp. 1708-1723
Author(s):  
M Akraminia ◽  
MJ Mahjoob ◽  
M Ghadami
Keyword(s):  
Noise Control ◽  
Active Noise Control ◽  
Second Order ◽  
Experimental Results ◽  
Superior Performance ◽  
Infinite Impulse Response ◽  
Gradient Descent Method ◽  
Adaptive Wavelet ◽  
Wavelet Networks ◽  
Active Noise

An active noise control algorithm is introduced based on adaptive wavelet networks using rationale functions with second-order poles wavelets. A novel network structure is derived using a nonlinear static mapping cascaded with an infinite impulse response filter wherein only input at the current step is needed to generate the output of the next sample. Therefore, incorporating tap delayed line of input–output of the physical system can be eliminated, avoiding the use of multidimensional wavelet networks. Online dynamic back-propagation learning algorithms (based on gradient descent method) are applied to adjust the network parameters. The local convergence of the closed-loop system is proved using discrete Lyapunov function. Simulations are carried out to compare the performance of proposed methods with other nonlinear algorithms (e.g. FxBPNN, Volterra, FLNN, and RFFLNN). Experiments are then conducted to evaluate the developed algorithms. Both simulation and experimental results show the superior performance of proposed method in terms of fast convergence rate and noise attenuation while avoiding curse of dimensionality.

Design and Implementation of Self-Tuning Regulators for Active Noise Control

1991 ◽  
Author(s):  
Rahmat Shoureshi ◽  
Yasuhiro Matsuyoshi
Keyword(s):  
High Frequency ◽  
Noise Control ◽  
Acoustic Noise ◽  
Active Noise Control ◽  
Frequency Noise ◽  
Control Methods ◽  
Active Noise ◽  
Self Tuning ◽  
Passive Noise ◽  
Industrial Societies

Abstract Acoustic noise has become an increasingly important problem, especially in industrial societies. The main reason being the increase in usage of machines in virtually all aspects of our lives, higher population densities, and concerns about the health consequences of exposure to acoustic noise. Passive noise control methods work well for relatively high frequency noise, but become progressively more expensive and less effective as one considers control of lower frequency noise. Development and implementation of an adaptive active noise controller is presented.

Inversion-Based Feedforward Approach to Broadband Acoustic Noise Reduction

2008 ◽  
Vol 130 (5) ◽  
Author(s):  
Tom C. Waite ◽  
Qingze Zou ◽  
Atul Kelkar
Keyword(s):  
Noise Control ◽  
Feedforward Control ◽  
Acoustic Noise ◽  
Active Noise Control ◽  
Low Frequency ◽  
Control Technique ◽  
Frequency Range ◽  
Nonminimum Phase ◽  
Control Approach ◽  
Active Noise

In this article, an inversion-based feedforward control approach to achieve broadband active-noise control is investigated. Broadband active-noise control is needed in many areas, from heating, ventilation and air conditioning (HVAC) ducts to aircraft cabins. Achieving broadband active-noise control, however, is very challenging due to issues such as the complexity of acoustic dynamics (which has no natural roll-off at high frequency, and is often nonminimum phase), the wide frequency spectrum of the acoustic noise, and the critical requirement to overcome the delay of the control input relative to the noise signal. These issues have limited the success of existing feedforward control techniques to the low-frequency range of [0,1]kHz. The modeling issues in capturing the complex acoustic dynamics coupled with its nonminimum-phase characteristic also prevent the use of high-gain feedback methods, making the design of an effective controller to combat broadband noises challenging. In this article, we explore, through experiments, the potential of inversion-based feedforward control approach for noise control over the 1kHz low-frequency range limit. Then we account for the effect of modeling errors on the feedforward input by a recently developed inversion-based iterative control technique. Experimental results presented show that noise reduction of over 10–15dB can be achieved in a broad frequency range of 5kHz by using the inversion-based feedforward control technique.

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