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近场声全息正则化方法比较
引用本文:陈达亮,舒歌群,卫海桥.近场声全息正则化方法比较[J].天津大学学报(自然科学与工程技术版),2008,41(6):696-702.
作者姓名:陈达亮  舒歌群  卫海桥
作者单位:天津大学内燃机燃烧学国家重点实验室,天津300072
摘    要:为了正确选择正则化方法,在基于边界元方法的近场声全息理论基础上,分析了截断奇异值法和Tikhonov正则化方法的异同点,阐述了通过曲率求解L曲线拐角点的基本原理,并将L曲线准则和广义交叉检验法应用于截断奇异值正则化方法最优截断点的选取.通过数值仿真表明,利用L曲线最大曲率点可以有效地确定L曲线最优正则化参数位置;在基于边界元法的共形平面近场声全息中,当信噪比为60dB时,4种组合正则化方法在l000Hz频率点处分辨距离能达到42mm最后,比较研究了4种组合正则化方法的重构精度和稳健性.

关 键 词:近场声全息  正则化疗法  边界元方法  截断奇异值法  Tikhonov法  L曲线准则  广义交义检验法

Comparison of Regularization Methods of Nearfield Acoustic Holography
CHEN Da-liang,SHU Ge-qun,WEI Hai-qiao.Comparison of Regularization Methods of Nearfield Acoustic Holography[J].Journal of Tianjin University(Science and Technology),2008,41(6):696-702.
Authors:CHEN Da-liang  SHU Ge-qun  WEI Hai-qiao
Institution:( State Key Laboratory of Engines, Tianjin University, Tianjin 300072, China)
Abstract:The selection of regularization methods is the key issue on the boundary element method ( BEM )-based nearfield acoustic holography ( NAH ). The characteristics of the truncated singular value decomposition ( TSVD ) method and standard Tikhonov regularization method were discussed respectively. The L-curve criterion and the generalized cross validation ( GCV ) method were both employed to attain the optimal regularization parameters for Tikhonov and TSVD regularization method. Furthermore, the maximum curvature of L-curve is used to determine the regularization parameter of the L-curve criterion. A numerical simulation of a speaker is taken as an example. The numerical results demonstrate the validity of the maximum curvature of L-curve applied in L-curve criterion. It can also be concluded that a signal noise ratio ( SNR ) of about 60 dB would lead to the resolution distance of 42 mm at the frequency of 1 000 Hz. Finally, the accuracy and limitation of four combined regularization methods are investigated.
Keywords:nearfield acoustic holography  regularization method  boundary element method  truncated singular value decomposition method  Tikhonovmethod  L-curvecriterion  generalized cross validation method
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