NEURAL NETWORKS METHOD IN PRESSURE GAUGE MODELING

Alexander Vasilyev, Dmitry Tarkhov, Gleb Guschin

Abstract

The mathematical model of an acoustic wave field in the measuring cavity of pressure calibrator is established. Two ways to the problem solution are posed. The system of two neural networks – RBF and perceptron – is applied to the working hole optimization and the wave field approximation. This new approach based on neural networks methodology seems to be adequate, effective and powerful: it is weakly sensitive to some entrance data perturbation, it gives trained neural networks for a set of problems solution, it is possible to use the same ideas in case of nonlinearity modeling.

Keywords

gauge, boundary optimization, neural networks

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IMEKO-TC7-2004-078.pdf

DOI

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IMEKO TC

TC7 - Measurement Science

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