Optimal Design for Induction Heating Using Genetic Algorithms

نویسندگان

  • TEODOR LEUCA
  • NISTOR DANIEL TRIP
  • HELGA SILAGHI
  • CLAUDIU MICH-VANCEA
چکیده

This paper presents an automatic design method of an optimal inductive heating system modeled by finite element method. To obtain a uniform temperature distribution to the work piece surface, the inductor’s wrapping step is optimized by means of genetic algorithms. The 3D numerical model is provided by the Flux tools. The paper presents an innovative optimization procedure based on the scripting capability of the Flux 3D software. The genetic algorithm is implemented in PyFlux, which is a combination of Python and Flux commands that allows users to control any aspect of the modeling process. The results obtained through combining Flux 3D software with genetic algorithms and PyFlux commands prove that the proposed method is suitable for automating optimal design of the induction heating equipments.

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تاریخ انتشار 2015