<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

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

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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...

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

Online veröffentlicht: 13. Sept. 2017

Seitenbereich: 299 - 305

Eingereicht: 06. Okt. 2016

DOI: https://doi.org/10.1515/jee-2017-0042

Schlüsselwörter
induction melting, melted material resistivity measurement, neural network

© Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Online veröffentlicht: 13. Sept. 2017

Seitenbereich: 299 - 305

Eingereicht: 06. Okt. 2016

DOI: https://doi.org/10.1515/jee-2017-0042

Schlüsselwörterinduction melting, melted material resistivity measurement, neural network

© Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
induction melting, melted material resistivity measurement, neural network