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Determination of Bubble Size Distribution using Ultrasound Array Imaging

Abstract

In this paper, ultrasonic phased arrays are deployed as an imaging tool for industrial process analysis. Such arrays are typically used for sonar, medical diagnosis and non-destructive testing, however, they have not yet been applied to industrial process analysis. The precise positioning of array elements and high frequencies possible with this technology mean that highly focused images can be generated that cannot currently be achieved using ultrasound tomography. This paper aims to highlight the potential of this technology for measurement of bubble size distribution (BSD) and to demonstrate its application to both intrusive and non-invasive process measurement. Ultrasound images of bubble reflectors are generated using the total focusing method deployed using a 32 element, 5 MHz linear phased array and an image processing algorithm for BSD determination is presented and evaluated under stationary and dynamic acquisition conditions. It is found that the sizing accuracy is within 10% for stationary reflectors larger than 4λ in diameter and that the algorithm is stable across the expected spatial variation of reflectors. The phased array is coupled to a six-axis robotic arm to scan a solid sample containing bubble reflectors at velocities up to 500 mms–1. The sizing accuracy is within 45% for bubbles larger than 4λ in diameter and at velocities up to 300 mms–1. However, above this velocity the algorithm breaks down for reflectors smaller than 9λ in diameter. The ultrasound system is applied to a stream of air bubbles rising through water that is verified via photographic analysis. Images were generated both intrusive and non-invasive, via a 10 mm Perspex barrier, to the process stream. The high bubble density in the process stream introduced scattering, limiting the measurement repeatability and the sample size in the measured distribution. Notwithstanding, this result demonstrates the potential of this technology to size bubbles for intrusive and non-invasive process analysis

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This paper was published in Explore Bristol Research.

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