scholarly journals Research on a noise control device. (5th report The noise reduction effect of application to a machine and its prediction method by a scale model experiment)

1986 ◽  
Vol 52 (483) ◽  
pp. 2863-2868
Author(s):  
Keiichiro MIZUNO ◽  
Hisayoshi SEKIGUTI ◽  
Kazuyoshi IIDA
2021 ◽  
Vol 263 (5) ◽  
pp. 1919-1928
Author(s):  
Xing Ren ◽  
Hongwei Zhang

Active noise control (ANC) has been intensively studied for decades. The most classical ANC algorithm should be the filtered-x least mean square (FxLMS) algorithm, which needs the model of the secondary path to work. Thus, the residual error of the ANC system is closely related to the preciseness of the secondary path model. In many applications, the secondary path is often time-varying. Therefore, off-line identification of the secondary path is not applicable. However, on-line identification often requires an additional white noise as a stimulating signal of the secondary path, which will deteriorate the final noise reduction effect. This paper proposes an improved artificial bee colony (ABC) algorithm for ANC system, which does not require identification of the secondary path. In order to guarantee the convergence of the algorithm and accelerate the convergence speed, this paper introduces a variable forgetting factor into the fitness function, and improves the traditional ABC algorithm by integrating LMS algorithm into the ABC algorithm. A single channel ANC system equipped with an FPGA hardware platform is set up in an anechoic chamber, and experiments show that the proposed algorithm can produce a satisfactory noise reduction effect without modeling the secondary path.


2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Leopoldo Pacheco Bastos ◽  
Gustavo da Silva Vieira de Melo ◽  
Newton Sure Soeiro

Noise control devices such as panels and barriers, when of high efficiency, generally are of difficult acquisition due to high costs turning in many cases their use impracticable, mainly for limited budget small-sized companies. There is a huge requirement for new acoustic materials that have satisfactory performance, not only under acoustic aspect but also other relevant ones and are of low cost. Vegetable fibers are an alternative solution when used as panels since they promise satisfactory acoustic absorption, according to previous researches, exist in abundance, and derive from renewable sources. This paper, therefore, reports on the development of panels made from vegetable fibers (coconut, palm, sisal, and açaí), assesses their applicability by various experimental (flammability, odor, fungal growth, and ageing) tests, and characterize them acoustically in terms of their sound absorption coefficients on a scale model reverberant chamber. Acoustic results point out that the aforementioned fiber panels play pretty well the role of a noise control device since they have compatible, and in some cases, higher performance when compared to commercially available conventional materials.


2021 ◽  
Vol 11 (9) ◽  
pp. 3869
Author(s):  
Chen Niu ◽  
Yongwei Liu ◽  
Dejiang Shang ◽  
Chao Zhang

Superhydrophobic surface is a promising technology, but the effect of superhydrophobic surface on flow noise is still unclear. Therefore, we used alternating free-slip and no-slip boundary conditions to study the flow noise of superhydrophobic channel flows with streamwise strips. The numerical calculations of the flow and the sound field have been carried out by the methods of large eddy simulation (LES) and Lighthill analogy, respectively. Under a constant pressure gradient (CPG) condition, the average Reynolds number and the friction Reynolds number are approximately set to 4200 and 180, respectively. The influence on noise of different gas fractions (GF) and strip number in a spanwise period on channel flow have been studied. Our results show that the superhydrophobic surface has noise reduction effect in some cases. Under CPG conditions, the increase in GF increases the bulk velocity and weakens the noise reduction effect. Otherwise, the increase in strip number enhances the lateral energy exchange of the superhydrophobic surface, and results in more transverse vortices and attenuates the noise reduction effect. In our results, the best noise reduction effect is obtained as 10.7 dB under the scenario of the strip number is 4 and GF is 0.5. The best drag reduction effect is 32%, and the result is obtained under the scenario of GF is 0.8 and strip number is 1. In summary, the choice of GF and the number of strips is comprehensively considered to guarantee the performance of drag reduction and noise reduction in this work.


1986 ◽  
Vol 29 (253) ◽  
pp. 2260-2265
Author(s):  
Hisayoshi SEKIGUCHI ◽  
Keiichiro MlZUNO ◽  
Kazuyoshi IIDA

2005 ◽  
Vol 128 (2) ◽  
pp. 148-155 ◽  
Author(s):  
Jesse B. Bisnette ◽  
Adam K. Smith ◽  
Jeffrey S. Vipperman ◽  
Daniel D. Budny

An active noise control device called active noise absorber or ANA, which is based upon damped, resonant filters is developed and demonstrated. It is similar to structural positive position feedback (PPF) control, with two exceptions: (1) Acoustic transducers (microphone and speaker) cannot be truly collocated, and (2) the acoustic actuator (loudspeaker) has significant dynamics. The speaker dynamics can affect performance and stability and must be compensated. While acoustic modal control approaches are typically not sought, there are a number of applications where controlling a few room modes is adequate. A model of a duct with speakers at each end is developed and used to demonstrate the control method, including the impact of the speaker dynamics. An all-pass filter is used to provide phase compensation and improve controller performance and permits the control of nonminimum phase plants. A companion experimental study validated the simulation results and demonstrated nearly 8 dB of control in the first duct mode. A multi-modal control example was also demonstrated producing an average of 3 dB of control in the first four duct modes.


2005 ◽  
Vol 49 ◽  
pp. 865-870
Author(s):  
Akinori NAKATA ◽  
Takashi NISHIZAWA ◽  
Junji ONISHI ◽  
Haruo SOEDA

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