Abstract
In a large water cavitation channel, the ability to differentiate between environmental noise and flow noise was previously unavailable. Through the use of holographic processing of hydrophone array data, the direction of the environmental noise is revealed, and enhanced beam-focusing capabilities are provided. At various flow speeds in the channel, the pressure data are acquired from a planar array residing in a trough below the measurement cross section of the channel. The pressure data are filtered, amplified, digitized, and then processed with a holographic algorithm implemented in MATLAB. The holographic algorithm is able to predict pressures and pressure distributions in the channel at various distances above the array and at various flow speeds in the channel. In this presentation, the large cavitation channel and the method used to acquire the channel’s flow data will be described. The holographic algorithm utilized in the data processing and for the analysis of the channel will be explained. The channel’s features revealed by the holographic analysis at various channel flow speeds will be presented, and the environmental noise and the flow noise found through this study will be discussed. The theoretical and observed array gains achieved by the holographic processing will be compared, and their use in enhancing the beam-focusing capabilities of the planar array will be described. [Work supported by CD/NSWC.]
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