The method for improving the reconstruction accuracy and computational speed of the statistically optimized nearfield acoustic holography

By analyzing the reconstruction process of the statistically optimized nearfield acoustic holography (SONAH), it is found that selecting regularization parameter too small is the essential reason for the low accuracy of SONAH when normal velocity on the surface of noise sources is reconstructed. In order to improve the reconstruction accuracy of SONAH, a method for optimized selection of elementary planar waves is proposed to guarantee the correct selection of the regularization parameter, in which all the propagating waves and parts of evanescent waves are retained and parts of the evanescent waves related to high wave number are eliminated. Moreover the order of the transfer matrix of SONAH decreases after using the proposed method, consequently the problem that the computational speed will become slow rapidly as soon as the number of measurement points increase can be solved simultaneously. The numerical simulation and the experiment are conducted to demonstrate the validity that both the reconstruction accuracy and the computational method of the proposed method, and the results of which show speed of SONAH are improved a lot by the proposed