Finite Element and Neural Network Approximations to Measure Forces Using Six-Component Wind Tunnel Balance

摘要

The aspects of building a transformation function for a multicomponent sensor based on the methods of finite element approximation of functions of several variables, as well as approximation using neural networks, are considered in this paper. Testing of mathematical models, computational methods and developed data processing algorithms was carried out on the experimental data of the calibration of a six-component "6TB203" sensor. The analysis of the obtained experimental data is carried out and the metrological characteristics of the sensor are determined. The computational algorithms for the use of the finite element and neural network approximations in modern measuring and computing systems have been developed and tested. It is shown that the use of finite element and neural network approximation allows one to improve the measurement results.