scholarly journals Reduction of low-frequency resonance utilizing active noise control system in enclosed three-dimensional space

2012 ◽  
Vol 33 (2) ◽  
pp. 106-108
Author(s):  
Ken Kaneuchi ◽  
Koichi Nishimura
Keyword(s):  
Control System ◽  
Noise Control ◽  
Dimensional Space ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Low Frequency ◽  
Frequency Resonance ◽  
Active Noise ◽  
Three Dimensional Space

scholarly journals Study on Active Noise Control in Three-dimensional Space for Engine noise

2000 ◽  
Vol 2000.10 (0) ◽  
pp. 53-56
Author(s):  
Akihiko ENAMITO ◽  
Masaaki HIRAYAMA ◽  
Kazumasa TAKEMURA ◽  
Masamichi IPPOMMATSU ◽  
Kazuo TANAKA
Keyword(s):  
Noise Control ◽  
Dimensional Space ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Engine Noise ◽  
Active Noise ◽  
Three Dimensional Space

Experimental Study on an Active Noise Control System for Turboprop Driven Aircraft

2013 ◽  
Vol 333-335 ◽  
pp. 2142-2145
Author(s):  
Qing Fu Kong ◽  
Yu Liang Dai ◽  
Shi Jian Zhu ◽  
Jia Ming Wu
Keyword(s):  
Experimental Study ◽  
Control System ◽  
Sound Source ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Experimental Platform ◽  
Active Noise

In order to find a solution to the control of low frequency noise in the cabin of turboprop driven aircraft, an experimental active noise control (ANC) system is introduced in the paper, which consists of vibroacoustic field analogue subsystem, acoustic field measurement subsystem and acoustic barrier exciter subsystem. Effects of both different spaces between the primary sound source and secondary sound source of the ANC system and different frequency noises on noise-reduction result are investigated based on the experimental platform. Results of the experiment show a significant potential of the ANC method for the control of low frequency noise in the cabin of turboprop driven aircraft.

Optimal parametric design of delayless subband active noise control system based on genetic algorithm optimization

2021 ◽  
pp. 107754632110016
Author(s):  
Guo Long ◽  
Yawen Wang ◽  
Teik C Lim
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Noise Control ◽  
Parametric Design ◽  
Active Noise Control ◽  
Low Frequency ◽  
Broadband Noise ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Active Noise

Active noise control systems are generally application-specific, and an appropriate algorithm with an optimal configuration is desirable in the first stage of active noise control system design and deployment. This study presents a design of the subband active noise control system with optimal parameters for a practical broadband active noise control. Although the delayless subband active noise control has gained wide attention for broadband noise cancellation, an optimal design remains a challenge because of the complex interplay between multiple factors such as spectral leakage, delay and weight stacking distortion subject to a number of configurable parameters, and weight stacking method. The configurable parameters can hardly be optimized independently because the active noise control performance depends on the combined configuration. A simple near black box active noise control algorithm optimization model is thus established by incorporating the genetic algorithm optimization into the parametric design of the delayless subband algorithm. The automated process does not require an understanding of the performance characteristics for different parameters. The significance of applying the automated genetic algorithm optimization to the complex multiparameter nonlinear active noise control design is revealed by numerical simulations, particularly for the multichannel low-frequency broadband active noise control system configured with the delayless subband algorithms. This provides a way for the optimal parametric design of subband active noise control before being used in a practical complex scenario.

Simulation of Active Noise Control System on the Truck Interior Cab

2013 ◽  
Vol 798-799 ◽  
pp. 443-447
Author(s):  
Qi Chen LU ◽  
Hui Bin LI ◽  
Hua Huang
Keyword(s):  
Control System ◽  
Control Systems ◽  
Active Control ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Frequency Noise ◽  
Simulink Model ◽  
Active Noise ◽  
Active Control System

Studying on adaptive active noise control (AANC) system of the truck interior cab to reduce the low-frequency noise,a normalization FLMS algorithm simulink model is established in Matlab/Simulink.Then taking it as the core,a feedforward adaptive active control system and a feedback adaptive active control system of the tuck interior cab are established in Matlab/Simulink .Considerating the actual error channels effects on systems ,the noise reduction effects of two adaptive active control systems are verified from the simulintion results.Through comparing the two wo adaptive active control systems,we found that the feedforward adaptive active control system is more stable.

Development of Engine Exhaust Active Noise Control System

2014 ◽  
Vol 986-987 ◽  
pp. 1196-1200
Author(s):  
Jie Wang ◽  
Zhi En Liu ◽  
Jia Wei Zeng ◽  
Chao Wang
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Signal Acquisition ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Engine Exhaust ◽  
Voice Signal ◽  
Active Noise

In order to enhance the capacity of elimination of engine exhaust low frequency noise, a set of engine exhaust active noise control system was developed. The system was developed by using MC9S12XS128 MCU, and it is based on the theory of sound wave interference. The system can realize the voice signal acquisition, reverse phase processing and output, and can eliminate engine exhaust low frequency noise. Experimental results showed that the system has good silencing effects on the engine exhaust noise under the steady state.

scholarly journals Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Liang Wang ◽  
Woon Seng Gan ◽  
Sen M. Kuo
Keyword(s):  
Control System ◽  
Noise Suppression ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Audio Signal ◽  
Digital Signal ◽  
Processing Technologies ◽  
Active Noise

With the advancement of digital signal processing technologies, consumers are more concerned with the quality of multimedia entertainment in automobiles. In order to meet this demand, an audio enhancement system is needed to improve bass reproduction and cancel engine noise in the cabins. This paper presents an integrated active noise control system that is based on frequency-sampling filters to track and extract the bass information from the audio signal, and a multifrequency active noise equalizer to tune the low-frequency engine harmonics to enhance the bass reproduction. In the noise cancellation mode, a maximum of 3 dB bass enhancement can be achieved with significant noise suppression, while higher bass enhancement can be achieved in the bass enhance mode. The results show that the proposed system is effective for solving both the bass audio reproduction and the noise control problems in automobile cabins.

scholarly journals Optimization of Secondary Sources Configuration in Two-Dimensional Space Based on Sound Field Decomposition and Sparsity-Inducing Regularization

2019 ◽  
Vol 37 (4) ◽  
pp. 697-703
Author(s):  
Kean Chen ◽  
Jian Xu ◽  
Lei Wang ◽  
Bing Zhou
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Noise Control ◽  
Dimensional Space ◽  
Active Noise Control ◽  
Sound Field ◽  
Optimization Methods ◽  
Secondary Sources ◽  
Active Noise ◽  
Configuration Information

During the design of transducers configuration for an active noise control system, current optimization methods need to predetermine the error sensors configuration, which significantly increases the workload of later optimization of the secondary sources configuration. In this study, a new method free from specific error sensors configuration information is presented that higher order microphones are used to capture the sound field so as to formulate the cost function in wave domain. In addition, according to sparsity characteristics of the primary sound field, sparsity-inducing regularization is introduced to optimize the secondary sources configuration, including the number and positions, by calculating a sparse approximate solution to underdetermined equations. Effects of the number of candidate secondary sources are discussed, and the comparison with the uniform configuration and the optimized configuration using the genetic algorithm is performed. Results show that the proposed method can optimize the secondary sources configuration effectively independent of the error sensors configuration information. The noise reduction of the proposed method is close to that by the genetic algorithm, while other evaluation metrics for the system are much better, which would benefit the stability of active noise control system.

scholarly journals Experience With Active Control of Exhaust Noise From a Large Frame Combustion Turbine

1997 ◽  
Author(s):  
Lisa A. Beeson ◽  
George A. Schott
Keyword(s):  
Control System ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Heat Rate ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Residential Areas ◽  
Active Noise ◽  
Exhaust Noise

Low frequency noise generated by combustion turbine exhaust is one of the most difficult environmental impacts to control. When a combustion turbine power plant is located near residential areas or other sensitive receptors, it is imperative to minimize the low frequency noise being emitted. In the past, available technology was limited to passive and reactive silencers and massive enclosures or barrier walls. These techniques are expensive and can have significant impacts on megawatt output and heat rate. Active noise control technology offers an alternative for applications near sensitive receptors. An active noise control system was installed on the exhaust stack of a combustion turbine with an objective to cancel exhaust noise at frequencies below 35 Hertz (Hz). Unlike passive and reactive low frequency silencing, the active noise control system does not impact combustion turbine performance. The technology can be applied to new apparatus and can be retrofit to existing facilities with minimal changes to the design.

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