本文關(guān)鍵詞：基于自適應(yīng)濾波及模態(tài)分析的有源噪聲控制方法研究　出處：《西安電子科技大學》2014年博士論文　論文類型：學位論文

  更多相關(guān)文章： 前饋有源噪聲控制 結(jié)構(gòu)聲輻射控制 自適應(yīng)濾波 模態(tài)分析

【摘要】：隨著經(jīng)濟的發(fā)展和社會的進步，噪聲污染日益嚴重，，危害人們的身心健康，引起機械設(shè)備結(jié)構(gòu)的聲疲勞，并降低武器裝備的作戰(zhàn)性能和聲隱身性能。因此噪聲控制在民用和軍事領(lǐng)域中都具有十分重要的意義。有源噪聲控制技術(shù)是控制低頻噪聲的有效方法，根據(jù)噪聲控制機理可分為聲源控制、傳播途徑控制和接受者保護三類，研究內(nèi)容和手段具有多樣性。論文從接受者保護和聲源控制的角度出發(fā)，針對基于自適應(yīng)濾波技術(shù)的前饋有源噪聲控制方法和基于模態(tài)分析的結(jié)構(gòu)聲輻射控制方法中存在的一些主要問題開展研究工作。論文所做主要工作概況如下： 1.在自適應(yīng)前饋有源控制技術(shù)中，非因果成分會降低噪聲控制性能，為了使系統(tǒng)盡量滿足因果約束，提出一種參考信號的拾取方法。該方法將參考傳聲器放置在噪聲源來波方向上，并通過距離調(diào)整來增大參考傳聲器和誤差傳聲器的時間延遲，用于抵消串擾和反射等因素引起的非因果成分，從而提高噪聲控制性能。在此方法中，為了檢測寬帶噪聲源的來波方向，提出了一種基于KR積的內(nèi)插聚焦估計算法。該算法將各頻率點的協(xié)方差矩陣進行KR積擴展后，借助最小二乘內(nèi)插聚焦矩陣，構(gòu)造無噪聲聚焦后的各頻率數(shù)據(jù)組合矩陣，進而采用MUSIC方法實現(xiàn)過定和欠定兩種情況下的來波方向估計。最后，將噪聲源的定位結(jié)果用于指導參考傳聲器的布放，通過比較傳聲器布放位置及數(shù)目調(diào)整前后的噪聲控制效果，驗證參考信號拾取方法的有效性。 2.在寬帶噪聲的自適應(yīng)前饋有源控制技術(shù)中，無延遲子帶自適應(yīng)濾波方法由于能避免信號通道的延遲且收斂速度快，成為寬帶噪聲控制中的主要方法。但該方法的控制效果會受到分析濾波器組的群延遲和帶內(nèi)混疊誤差的影響，因此分析濾波組的設(shè)計是關(guān)鍵�，F(xiàn)有的分析濾波器組是調(diào)制線性相位原型低通濾波器得到的，它不能保證濾波器組的低群延遲和小旁瓣效應(yīng)，致使噪聲控制效果不明顯。為此，提出迭代二階錐規(guī)劃方法設(shè)計分析濾波器組。將帶內(nèi)混疊誤差和群延遲構(gòu)造為關(guān)于原型濾波器權(quán)系數(shù)的二次函數(shù)，進而通過迭代二階錐優(yōu)化得到原型濾波器權(quán)系數(shù)，最后利用均勻DFT調(diào)制為分析濾波器組。與同階線性相位分析濾波器組相比，該濾波器組具有更低的群延遲和更小的帶內(nèi)混疊誤差。在此基礎(chǔ)上，采用部分子帶權(quán)系數(shù)更新的歸一化最小均方誤差算法，構(gòu)建了頻域無延遲噪聲控制系統(tǒng)。實驗結(jié)果表明，該系統(tǒng)的噪聲控制效果明顯，不僅能有效降低殘余噪聲功率譜，提高噪聲衰減量，而且還具有收斂速度快和計算復雜度低等優(yōu)點。 3．在窄帶噪聲的自適應(yīng)前饋有源控制技術(shù)中，從理論上分析了頻率偏差造成自適應(yīng)濾波器權(quán)系數(shù)的均值偏移不能收斂到零矢量，是導致控制性能惡化的根本原因。因此為了提高噪聲控制效果，必須對干擾信號的頻率進行精確估計。為此，提出了一種用于實值信號的快速子空間跟蹤-ESPRIT類頻率估計方法。該方法的信號子空間維數(shù)與信號頻率的個數(shù)相等，從而避免了傳統(tǒng)方法用于實值頻率估計時，信號子空間的維數(shù)為頻率個數(shù)2倍的問題。仿真結(jié)果表明算法的精度高，滿足實際應(yīng)用的要求。最后，結(jié)合不需要次級通道估計的FXLMS算法，在DSP平臺上實現(xiàn)了彈性薄板的基頻和諧波分量的振動控制，從而降低了封閉聲腔中的結(jié)構(gòu)聲輻射的聲壓級。 4．在基于模態(tài)分析的彈性結(jié)構(gòu)聲輻射的控制技術(shù)中，根據(jù)輸入輸出測量數(shù)據(jù)建立精確受控系統(tǒng)模型是實施該類控制方法的前提。目前，主要采用子空間辨識方法來建立系統(tǒng)狀態(tài)方程，但該方法計算量大，難以得到有效應(yīng)用。為此，利用廣義能觀矩陣的列空間與觀測矢量相關(guān)矩陣的信號子空間一致的特征，提出了一種在線子空間辨識方法用于系統(tǒng)狀態(tài)方程的建立。該方法包含了兩個遞推過程：一是利用矩陣求逆變換計算觀測矢量；二是基于多級分解冪迭代子空間跟蹤算法估計廣義能觀矩陣，以保證按指數(shù)全局收斂到主子空間。仿真結(jié)果表明該方法能提高辨識精度，不僅減小廣義能觀矩陣估計值與真實值的夾角，還能降低辨識得到的輸出數(shù)據(jù)與真實值之間的均方根誤差。最后，利用有限元和聲學分析軟件，構(gòu)建了一種基于振動控制的封閉空間降噪系統(tǒng)模擬環(huán)境。采用所提的在線子空間辨識法建立了壓電結(jié)構(gòu)系統(tǒng)模型，結(jié)合線性二次最優(yōu)控制方法產(chǎn)生壓電陶瓷作動器次級電壓。通過控制與聲模態(tài)耦合大的結(jié)構(gòu)模態(tài)，有效降低了艙室結(jié)構(gòu)聲輻射的聲壓級，驗證了在線子空間辨識方法應(yīng)用在結(jié)構(gòu)聲輻射控制中的有效性。
[Abstract]:With the development of economy and the progress of the society, noise pollution and harm people's physical and mental health, caused by fatigue structure of mechanical equipment, and operational performance and reduce weaponry stealth performance. So the noise control is very important in civil and military field. The active noise control technology is an effective method to control the low frequency according to the noise, the noise control mechanism can be divided into control source, transmission and receiver protection three, research contents and methods of diversity. The protection from the recipient and source control angle, aiming at some main problems of adaptive filtering feedforward active noise control method and radiation control of structural acoustic modal analysis based on the method based on the research work done in this paper. The main work are summarized as follows:
1. in the feedforward adaptive active control technology, non causal components will reduce the noise control performance, in order to enable the system to meet the causality constraint, proposes a method for picking up the reference signal. This method will be placed in the reference microphone noise source to the wave direction, and through adjusting the distance to increase the reference microphone and microphone error time delay. For the non causal components offset caused by crosstalk and reflection and other factors, so as to improve the noise control performance. In this method, in order to detect the broadband noise source to wave direction, we propose a KR based product focusing interpolation estimation algorithm. The algorithm makes the covariance matrix of each frequency of KR product extension, by using the least squares interpolation focusing matrix, the frequency of data combination matrix without noise after focusing, and then using the MUSIC method to achieve a fixed and underdetermined two cases to estimate the wave direction. After that, the location result of noise source is used to guide the placement of reference microphone. The effectiveness of the reference signal pickup method is verified by comparing the noise control effect before and after adjusting the location and number of microphone placement.
2. control feedforward adaptive active noise in broadband technology, delayless subband adaptive filtering method can avoid the delay due to the signal channel and the convergence speed, and become the main method of broadband noise control. But the control effect will be affected by the analysis filters group delay and band aliasing error, therefore analysis and design of filter group is the key. The analysis filters the existing modulation is a linear phase prototype low-pass filter is obtained, it can not guarantee that the low group filter group delay and small sidelobe effects, resulting in the noise control effect is not obvious. Therefore, the analysis filter bank design iteration two order cone programming method. The band aliasing the group delay error and constructed as a quadratic function of the prototype filter coefficients, and then through the iteration of two order cone optimization prototype filter coefficients, finally using uniform DFT modulation Analysis of filter group. With the same order linear phase filter analysis compared with internal aliasing error of the filter has lower group delay and smaller. On this basis, the part of the sub coefficient updating weighted normalized least mean square error algorithm, constructed the frequency domain without delay noise control system. Experimental results show that the noise control effect of the system is obvious, not only can effectively reduce the residual noise power spectrum, improve the noise attenuation, but also has the advantages of fast convergence and low computational complexity.
3. control feedforward adaptive active noise in narrowband technology, the mean shift cannot converge from the theoretical analysis of the frequency deviation caused by the adaptive filter coefficients to zero vectors is to control root cause of performance deterioration. So in order to improve the noise control effect, to accurately estimate the frequency of interference signal. Therefore, put forward a for real valued signal fast subspace tracking -ESPRIT frequency estimation method. The number of signal subspace dimension and signal frequency of this method is the same, so as to avoid the traditional method for real valued frequency estimation, the dimension of the signal subspace is 2 times the number of frequency. The simulation results show that the algorithm has high precision, meet the requirement of practical application. Finally, combined with the FXLMS algorithm without the secondary path estimation, in the DSP platform to achieve the fundamental frequency and harmonic components of elastic thin plate Control, thereby reducing the sound pressure level in the enclosure structure acoustic radiation.
4. based on the control technology of elastic structural acoustic radiation modal analysis, according to the input and output measurement data to establish a precisely controlled system model is a prerequisite for the implementation of the control method. At present, mainly to establish the state equation of the system using subspace identification methods, but the computation amount is large, it is difficult to get the effective application. Therefore, the use of features the signals associated with the column space observation vector matrix generalized observability matrix space consistent, a method of online subspace identification is used to establish the state equation of the system is presented. This method includes two processes: one is to use recursive matrix inverse calculation of observation vector; two is the power iteration subspace decomposition the tracking algorithm to estimate the generalized observability matrix based on exponential to ensure global convergence to the principal subspace. The simulation results show that this method can improve the identification accuracy, not only can reduce the generalized The angle between the estimated value and the true value of the view matrix, but also can reduce the root mean square error between the output data and the actual identification value obtained. Finally, using finite element and acoustic analysis software to build a simulation environment for closed space noise reduction system of vibration control. Based on the established model of piezoelectric structure system using online subspace identification method the combination of two linear optimal control method to produce piezoelectric ceramic actuator. Through the coupling of secondary voltage control and modal acoustic modes in large, effectively reducing the sound pressure level of cabin structure acoustic radiation, verify the effectiveness of the application of online subspace identification method in the control of structural acoustic radiation.

【學位授予單位】：西安電子科技大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TN911.4;TN713

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