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Application of neural network for real-time measurement of electrical resistivity in cold crucible

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The article describes use of an Induction furnace with cold crucible as a tool for real-time measurement of a melted material electrical resistivity. The measurement is based on an inverse problem solution of a 2D mathematical model, possibly implementable in a microcontroller or a FPGA in a form of a neural network. The 2D mathematical model results has been provided as a training set for the neural network. At the end, the implementation results are discussed together with uncertainty of measurement, which is done by the neural network implementation itself.

eISSN:
1339-309X
Langue:
Anglais
Périodicité:
6 fois par an
Sujets de la revue:
Engineering, Introductions and Overviews, other