南方能源建设 (Jun 2022)

Boundary Reconstruction of Tokamak Plasma Based on Deep Neural Networks

  • Jiayi LI,
  • Shunping GU,
  • Mengjun GU,
  • Heng ZHANG,
  • Rui SHA

DOI
https://doi.org/10.16516/j.gedi.issn2095-8676.2022.02.010
Journal volume & issue
Vol. 9, no. 2
pp. 77 – 81

Abstract

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[Introduction] In order to realize the real-time reconstruction of plasma shape and position in tokamak, a visible light edge reconstruction algorithm based on fully connected neural network is proposed based on the analysis of camera calibration algorithm. [Method] The function of the algorithm was to establish the corresponding relationship between the pixel coordinate system and the tokamak coordinate system, and then realize the plasma visible light edge reconstruction. [Result] On the basis of the algorithm, few-shot learning is added to further improve the reconstruction algorithm of fully connected neural network. [Conclusion] Experimental results show that the algorithm can accurately reconstruct the plasma visible light edge, and also meet the real-time requirements of the system.

Keywords