121 Improvement in Noise Attenuation of Active Noise Control Unit

2011 ◽  
Vol 2011.21 (0) ◽  
pp. 75-78
Author(s):  
Xun WANG ◽  
Shinya KIJIMOTO ◽  
Koichi MATSUDA ◽  
Yosuke KOBA
2014 ◽  
Vol 496-500 ◽  
pp. 1685-1689
Author(s):  
Huai Feng Cui ◽  
Nan Chen

Multi-agent based active noise control (ANC) is investigated in this paper. An enclosure consisting of two flexible plates is discussed. The noise control problem is decomposed into several local control problems on the basis of the dominant structural modal. Each local control problem is solved by an intelligent structure, i.e. agent control unit (ACU). The ACU includes sensor, actuator and controller. The relationship among the ACUs is negotiated by a coordination object. The architecture of multi-agent based active control is established using the coordination object. The control system can work smoothly in dynamic environments. It has the flexibility and robustness. The simulation results indicate that the good control performances are attained.


Author(s):  
Oscar R. Flotte-Hernández ◽  
Alejandro Pineda-Olivares ◽  
Graciano Dieck-Assad ◽  
Alfonso Avila-Ortega ◽  
Sergio O. Martínez-Chapa ◽  
...  

2002 ◽  
Vol 112 (5) ◽  
pp. 2428-2428
Author(s):  
Rosely V. Campos ◽  
Rodrigo C. Ivo ◽  
Eduardo B. Medeiros

2011 ◽  
Vol 347-353 ◽  
pp. 2347-2350 ◽  
Author(s):  
Jiang Tao Liu ◽  
Li Ming Ying ◽  
Chun Ming Pei

The problem of noise in power transformer was pay attention to by this paper. The paper presents the design methodology for the active noise control (ANC) of sound disturbances in power transformer. The active noise attenuation algorithm uses the framework of output-error based optimization of a linearly parameterized filter for feedforward sound compensation to select optimal location of sensor and demonstrate the effectiveness of active noise attention in a large power transformer. The ANC controller can automatically measure the sound disturbances and select the compensate parameters to realize the noise cancellation. With 220kV power transformer noise cancellation, for example, the simulating results prove that the ANC technology to cancel the noise in power transformer is an effective way.


2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Daniele Pochi ◽  
Roberto Fanigliulo ◽  
Lindoro Del Duca ◽  
Pietro Nataletti ◽  
Gennaro Vassalini ◽  
...  

In last years, several research teams pointed their attention on the application of active noise control systems (ANC) inside the cabs of agricultural tractor, with the purpose of reducing the driver exposition to noise, that is only partially controlled by the frame of the cab. This paper reports the results of a first experience that aimed at verifying the applicability of an ANC on a medium-high power, tracked tractor without cab. The tested tractor was a Fiat Allis 150 A, equipped with rear power take off, used in the execution of deep primary tillage in compact soils. It is a tracked tractor without cab, with maximum power of 108.8 kW at 1840 min–1 of the engine. The ANC consists of a control unit box based on a digital signal processor (DPS), two microphones, two speakers and a power amplifier. The instrumentation used in noise data collecting and processing consisted of a multichannel signal analyzer (Sinus - Soundbook), a ½” microphone capsule and an acoustic calibrator, both Bruel & Kjaer. The study aimed at evaluating the behaviour of the ANC by means of tests carried out under repeatable conditions, characterized by pre-defined engine speed values. Three replications have been made for each engine speed. The sampling time was 30 s. Two series of tests were performed in order to compare the results observed with the ANC on and off. The engine speed adopted in the study ranged from 600 min– 1, up to 2000 min–1 (maximum speed) with steps of 100 min–1. The ANC proved to be effective in the interval of speed between 1400 and 1700 min–1, where the samplings have been intensified, adopting steps of 50 min–1. In such an interval, the attenuation observed with the ANC system on appeared evident both as weighed A sound pressure level (from 1.29 up to 2.46 dB(A)) and linear (from 4.54 up to 8.53 dB). The best performance has been observed at the engine speed of 1550 min–1, with attenuations, respectively of 2.46 dB(A) and 7.67 dB. Outside of the engine speed interval 1400 - 1700 min–1, the attenuations always resulted lower than 1 dB(A) for the weighed A sound pressure level and between 0.66 and 7.72 dB.


2018 ◽  
Vol 9 (4) ◽  
pp. 47-64
Author(s):  
Rodrigo P. Monteiro ◽  
Gabriel A. Lima ◽  
José P. G. Oliveira ◽  
Daniel S. C. Cunha ◽  
Carmelo J. A. Bastos-Filho

The excessive exposure to certain kinds of acoustic noise can lead to health problems. To avoid this situation, the use of noise attenuation devices is a standard solution. Among those devices, the active noise control (ANC) systems have gained prominence over the years, mainly due to the technological development and costs reduction of electronic components. Despite good performance of ANC concerning low-frequency noise attenuation, the convergence speed for this kind of system is still an important issue when it deals with real-time applications in dynamic environments. This article presents an alternative solution to accelerate the active attenuation system response. This solution is based on the use of sets of coefficients, which are employed during the adaptive filter initialization and are obtained via a training process with particle swarm optimization (PSO). Two objective functions were tested: one based on the response time itself and the other one based on the magnitude reduction of the residual noise. The coefficients obtained through this process provided response time reductions up to 98.3% concerning adaptive filters initialized with null coefficients. The article is an extended version of the conference paper Accelerating the Convergence of Adaptive Filters for Active Noise Control Using Particle Swarm Optimization, published in LA-CCI 2017.


Acoustics ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 354-363
Author(s):  
Jun Yuan ◽  
Jun Li ◽  
Anfu Zhang ◽  
Xiangdong Zhang ◽  
Jia Ran

This paper presents an algorithm structure for an active noise control (ANC) system based on an improved equation error (EE) model that employs the offline secondary path modeling method. The noise of a compressor in a gas station is taken as an example to verify the performance of the proposed ANC system. The results show that the proposed ANC system improves the noise reduction performance and convergence speed compared with other typical ANC systems. In particular, it achieves 28 dBA noise attenuation at a frequency of about 250 Hz and a mean square error (MSE) of about −20 dB.


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