摘要
统计最优近场声全息技术是通过全息面上测量声压的线性叠加来反演重建面上的声学量,可以从理论上克服基于傅氏变换的近场声全息技术的局限性。针对水中圆柱体的噪声源识别问题,采用声压和质点振速测量来进行声全息计算,推导了基于振速测量的统计最优柱面近场声全息技术的重建公式。利用所编制的程序进行了仿真验证,最后设计矢量水听器进行水中全息实验,验证了该方法的可行性和准确性,实验结果表明,该技术在水中柱形声源辐射声场的噪声源识别和定位中有着明显的优势。
In statistically optimized near-field acoustical holography （SONAH）, the reconstructed acoustical field is obtained by a linear combination of the measured sound pressure data on holographic surface, so it could overcome the limitation of FFT-based NAH. Appling this method to identify the noise source of underwater cylindrical structures, the principle of the statistically optimized cylindrical near-field acoustical holography based on measurement of pressure and particle velocity was presented. The numerical simulations were conducted. The validity and correctness of vector hydrophone array was assessed by underwater near-field acoustic holography experiments. The results of experiments using vector hydrophone array show the merits of the underwater NAI-/ in the reconstruction of sound field and in the identification and localization of noise sources.
出处
《振动与冲击》
EI
CSCD
北大核心
2011年第8期225-229,共5页
Journal of Vibration and Shock
基金
中央高校基本科研业务费专项资金资助项目(HEUCFR1013)
关键词
近场声全息
声压
质点振速
统计最优
矢量阵
near-field acoustical holography
acoustic pressure
particle velocity
statistical optimization
vectorhydrophone array
