電腦風扇噪聲主動降噪關鍵技術研究
發(fā)布時間：2018-08-06 09:09
【摘要】：隨著互聯(lián)網技術的飛速發(fā)展,電腦已經成為了人們日常生活和工作中不可或缺的一部分,隨之而來的電腦風扇噪聲也越來越受到人們的重視。傳統(tǒng)的被動降噪方法在短時間內可以起到一定的降噪效果,但是實際中環(huán)境溫度的變化、風扇上灰塵的積累、風扇的老化等均會使降噪效果逐漸變差。而主動噪聲控制(Active Noise Control)可以通過自適應算法實時地響應風扇噪聲特性的變化,且對于低頻窄帶噪聲有著很好的降噪效果,故ANC技術在電腦風扇噪聲的控制上將會有較大的應用前景。 本文主要研究如何設計ANC系統(tǒng),確立其一般的設計流程以及在設計過程中所要解決的關鍵問題有哪些。通過研究,ANC系統(tǒng)的一般設計流程為：首先分析源噪聲特性,然后根據分析結果選擇合適的通道特性及控制特性。其中通道特性主要包括管道的尺寸、次級通道數量、電聲設備的空間分布,控制特性主要包括控制結構、控制算法、算法參數的選擇、誤差通道的辨識。最后根據通道特性及控制特性選擇合適的硬件設備。 文中主要研究了管道的設計、自適應的控制算法及自適應濾波器、傳感器和揚聲器的空間布置以及聲通道的自適應辨識。其中管道的設計依據聲波導管理論以及揚聲器和誤差傳感器位置的優(yōu)化；聲通道的辨識采用可控的離線自適應辨識方法。在控制算法上本文研究了三種算法,考慮到電腦風扇噪聲的特性以及管道尺寸較小,采用FbLMS算法作為ANC系統(tǒng)的控制算法,然后通過Matlab仿真確定算法參數對降噪效果的影響,并得到如下結論：收斂系數越大,系統(tǒng)收斂速度越快,但過大的收斂系數回事系統(tǒng)發(fā)散；濾波器長度越大,收斂速度越快,但會增加數據的吞吐量；算法對于窄帶噪聲有很好的降噪效果,但隨著帶寬的增加,降噪效果明顯下降；誤差通道傳遞函數的估計可以有一定的誤差,但不宜過大,否則系統(tǒng)發(fā)散。 最后為了驗證主動消聲理論與控制算法,搭建了硬件試驗平臺,并對模擬的正弦噪聲進行降噪,取得了一定的降噪效果。
[Abstract]:With the rapid development of Internet technology, computers have become an indispensable part of people's daily life and work, and the noise of computer fans has been paid more and more attention. The traditional passive noise reduction method can play a certain effect in a short period of time, but the change of environment temperature, the accumulation of dust on the fan and the aging of the fan will make the noise reduction effect worse gradually. The active noise control (Active Noise Control) can respond to the fan noise characteristics in real time by adaptive algorithm, and has a good noise reduction effect for low frequency narrow band noise. Therefore, ANC technology will have a great application prospect in the noise control of computer fan. This paper mainly studies how to design ANC system, how to establish its general design flow and what are the key problems to be solved in the design process. The general design flow of ANC system is as follows: firstly, the source noise characteristics are analyzed, and then the appropriate channel characteristics and control characteristics are selected according to the analysis results. The channel characteristics mainly include the size of pipeline, the number of secondary channels, the spatial distribution of electro-acoustic equipment, and the control characteristics mainly include control structure, control algorithm, algorithm parameter selection, error channel identification. Finally, according to the channel characteristics and control characteristics, select the appropriate hardware equipment. In this paper, the design of pipeline, adaptive control algorithm and adaptive filter, space arrangement of sensor and loudspeaker and adaptive identification of acoustic channel are studied. The design of the pipeline is based on the acoustic tube theory and the optimization of the speaker and error sensor position, and the sound channel identification adopts the controllable off-line adaptive identification method. Considering the noise characteristics of computer fan and the small size of pipeline, FbLMS algorithm is used as the control algorithm of ANC system, and then the effect of algorithm parameters on noise reduction is determined by Matlab simulation. The conclusions are as follows: the larger the convergence coefficient, the faster the system convergence speed, but the larger the convergence coefficient, the faster the convergence speed is, but the faster the data throughput is, and the larger the filter length is, the faster the convergence speed is. The algorithm has a good noise reduction effect for narrow band noise, but with the increase of bandwidth, the noise reduction effect is obviously reduced; the estimation of the error channel transfer function can have some errors, but not too large, otherwise the system diverges. Finally, in order to verify the active noise theory and control algorithm, a hardware test platform is built, and the simulated sinusoidal noise is de-noised, and the noise reduction effect is achieved.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP306.2;TB535.1
本文編號：2167236
[Abstract]:With the rapid development of Internet technology, computers have become an indispensable part of people's daily life and work, and the noise of computer fans has been paid more and more attention. The traditional passive noise reduction method can play a certain effect in a short period of time, but the change of environment temperature, the accumulation of dust on the fan and the aging of the fan will make the noise reduction effect worse gradually. The active noise control (Active Noise Control) can respond to the fan noise characteristics in real time by adaptive algorithm, and has a good noise reduction effect for low frequency narrow band noise. Therefore, ANC technology will have a great application prospect in the noise control of computer fan. This paper mainly studies how to design ANC system, how to establish its general design flow and what are the key problems to be solved in the design process. The general design flow of ANC system is as follows: firstly, the source noise characteristics are analyzed, and then the appropriate channel characteristics and control characteristics are selected according to the analysis results. The channel characteristics mainly include the size of pipeline, the number of secondary channels, the spatial distribution of electro-acoustic equipment, and the control characteristics mainly include control structure, control algorithm, algorithm parameter selection, error channel identification. Finally, according to the channel characteristics and control characteristics, select the appropriate hardware equipment. In this paper, the design of pipeline, adaptive control algorithm and adaptive filter, space arrangement of sensor and loudspeaker and adaptive identification of acoustic channel are studied. The design of the pipeline is based on the acoustic tube theory and the optimization of the speaker and error sensor position, and the sound channel identification adopts the controllable off-line adaptive identification method. Considering the noise characteristics of computer fan and the small size of pipeline, FbLMS algorithm is used as the control algorithm of ANC system, and then the effect of algorithm parameters on noise reduction is determined by Matlab simulation. The conclusions are as follows: the larger the convergence coefficient, the faster the system convergence speed, but the larger the convergence coefficient, the faster the convergence speed is, but the faster the data throughput is, and the larger the filter length is, the faster the convergence speed is. The algorithm has a good noise reduction effect for narrow band noise, but with the increase of bandwidth, the noise reduction effect is obviously reduced; the estimation of the error channel transfer function can have some errors, but not too large, otherwise the system diverges. Finally, in order to verify the active noise theory and control algorithm, a hardware test platform is built, and the simulated sinusoidal noise is de-noised, and the noise reduction effect is achieved.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP306.2;TB535.1
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