Surface temperature measurement from infrared synthetic diagnostic in preparation for ITER operations

Abstract

The protection of ITER in-vessel components and the plasma-wall interaction studies will be based on a large network of infrared (IR) cameras covering 70% of the tokamak. The surface temperature measurement from IR images remains challenging due to the presence of metallic targets, with changes in surface thermo-radiative properties (emissivity) and the presence of multiple reflections. The paper provides an overview of major progress to improve the interpretation of IR image and to get more reliable surface temperature from IR synthetic diagnostics. The paper presents the latest development of (1) the forward model to include the modelling of the edge localised modes and a new advanced camera that is better adapted to experimental data (2) the inverse model to retrieve the emissivity of the targets and the surface temperature from a neural network trained exclusively from synthetic IR images. Promising results have been obtained both from simulated test images with an estimated emissivity better than 0.05 and a surface temperature better than 10%, and from WEST experimental images of ITER-like wide-angle to filter reflection patterns.

Keywords

• synthetic diagnostic
• infrared
• wall protection
• neural network
• emissivity