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Modeling of the non-linear acoustic response of bubbles by Volterra series analysis

Lookup NU author(s): Dr Stephen Simmons, Emeritus Professor Oliver Hinton, Alan Adams


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The ability to determine the size distribution of a field of bubbles has a wide range of practical applications. Bubbles have traditionally been detected by using either optical or acoustic techniques. Bubbles exhibit strong acoustic resonance properties dependent on their size. By probing a field of bubbles it is possible to form an estimate of the range of sizes present by analysing the scattered data. There are a number of acoustic bubble sizing methods currently available, some of which exploit the non-linear dynamic behaviour of the bubble. By modeling this behaviour, improvements may be made to the estimation techniques. This paper presents estimates for the quadratic transfer function of a single bubble based on the Volterra series. A method of estimating the Volterra kernels using a neural network is presented which significantly reduces the quantity of data required to form an estimate of the transfer function.

Publication metadata

Author(s): Simmons SM, Hinton OR, Adams AE

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the 2000 IEEE International Conference on Acoustics, Speech and Signal Processing, 2000. ICASSP '00.

Year of Conference: 2000

Pages: 189-192

ISSN: 0780362934

Publisher: Institution of Electronic and Electrical Engineers


DOI: 10.1109/ICASSP.2000.861910