Statistically Optimized Cylindrical Near-Field Acoustic Holography Study Based on Measurement of Vector Hydrophone Array

Statistically optimized near-field acoustic holography (SONAH) is a new technique which is a variant of near-field acoustic holography (NAH). In SONAH, the reconstructed acoustic field is obtained from a weighted sum of the measured data on the holographic surface. Therefore, it could overcome the truncation errors posed by the spatial Fourier transform used in traditional NAH. Applying this method to identify the noise sources in underwater cylinder, the principle of the statistically optimized cylindrical near-field acoustic holography based on measurement of particle velocity was presented. A numerical simulation study has been carried out. Then an experiment has been conducted using vector hydrophone array. The experimental results show the great advantage of the SONAH in the reconstruction of sound field, as well as the identification and localization of noise sources.