Abstract
In this paper an architecture of a system for strain investigation and analysis over metals with remote access is proposed. The deformations of the test turners are measured by two strain gauges connected to adjacent arms of a Winston bridge. The models are examined with a high coefficient of determination R2 above level 0.98. The results according to synthesizing artificial neural networks in MATLAB environment about determination the amount of measuring transducers in detection the loads of experimental cantilever beam are presented. Two neural models with 9 and 6 hidden neurons about variables “Uout” and combination “F and Uout” with correct classification of test data were selected. Levels of the mean square error related to the synthesized neural network in two 9.9631e−04 compared to the network in one input parameter 0.0832 are observed, respectively.
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Malamatoudis, M., Kogias, P., Daskalaki, D., Sadinov, S. (2020). Communication System for Strain Analysis over Metals on the Base of Tensoresistor Transducers. In: Silhavy, R. (eds) Applied Informatics and Cybernetics in Intelligent Systems. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1226. Springer, Cham. https://doi.org/10.1007/978-3-030-51974-2_31
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DOI: https://doi.org/10.1007/978-3-030-51974-2_31
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