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[4, 2017] 

Journal of Electrical Engineering, Vol 68, 4 (2017) 299-305 DOI: 10.1515/jee-2017-0042

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

Pavel Votava – Igor Poznyak

   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.

Keywords: induction melting, melted material resistivity measurement, neural network


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