The distributed source boundary point method （DSBPM） is used as the spatial transform algorithm for realizing nearfield acoustic holography （NAH）, the sensitivity of the reconstructed solution to the measurement e...The distributed source boundary point method （DSBPM） is used as the spatial transform algorithm for realizing nearfield acoustic holography （NAH）, the sensitivity of the reconstructed solution to the measurement errors is analyzed, and the regularization method is proposed to stabilize the reconstruction process, control the influence of the measurement errors and get a better approximate solution. An oscillating sphere is investigated as a numerical example, the influence of the measurement errors on the reconstruction solution is demonstrated, and the feasibility and validity of the regularization method are validated. Key words： Acoustic holography Boundary point method Inverse problem Regularization展开更多
On the basis of the distributed source boundary point method (DSBPM)-based nearfield acoustic holography (NAH), Landweber iterative regularization method is proposed to stabilize the NAH reconstruction process, contro...On the basis of the distributed source boundary point method (DSBPM)-based nearfield acoustic holography (NAH), Landweber iterative regularization method is proposed to stabilize the NAH reconstruction process, control the influence of measurement errors on the reconstructed results and ensure the validity of the reconstructed results. And a new method, the auxiliary surface method, is pro- posed to determine the optimal iterative number for optimizing the regularization effect. Here, the optimal number is determined by minimizing the relative error between the calculated pressure on the auxiliary surface corresponding to each iterative number and the measured pressure. An experiment on a speaker is investigated to demonstrate the high sensitivity of the reconstructed results to measurement errors and to validate the chosen method of the optimal iterative number and the Landweber iterative regularization method for controlling the influence of measurement errors on the reconstructed results.展开更多
基金This project is supported by National Natural Science Foundation of China(No.50275044)Research Fund for Doctoral Program of Ministry of Education of China(No.20020359005).
文摘The distributed source boundary point method （DSBPM） is used as the spatial transform algorithm for realizing nearfield acoustic holography （NAH）, the sensitivity of the reconstructed solution to the measurement errors is analyzed, and the regularization method is proposed to stabilize the reconstruction process, control the influence of the measurement errors and get a better approximate solution. An oscillating sphere is investigated as a numerical example, the influence of the measurement errors on the reconstruction solution is demonstrated, and the feasibility and validity of the regularization method are validated. Key words： Acoustic holography Boundary point method Inverse problem Regularization
基金This work was supported by the National Natural Science Foundation of China （Grant No. 10504006）the Research Fund for the Doctoral Program of Higher Education （Grant No. 20020359005）.
文摘On the basis of the distributed source boundary point method (DSBPM)-based nearfield acoustic holography (NAH), Landweber iterative regularization method is proposed to stabilize the NAH reconstruction process, control the influence of measurement errors on the reconstructed results and ensure the validity of the reconstructed results. And a new method, the auxiliary surface method, is pro- posed to determine the optimal iterative number for optimizing the regularization effect. Here, the optimal number is determined by minimizing the relative error between the calculated pressure on the auxiliary surface corresponding to each iterative number and the measured pressure. An experiment on a speaker is investigated to demonstrate the high sensitivity of the reconstructed results to measurement errors and to validate the chosen method of the optimal iterative number and the Landweber iterative regularization method for controlling the influence of measurement errors on the reconstructed results.
