Abstract: Plasma emission spectroscopy is one of the important diagnostic methods to study the physics of plasma within tokamak. There are complex atomic and molecular physical processes in the boundary plasma, and some weaker particle spectrum signals are mixed with a lot of noise. Whether noise can be effectively removed and the signal quality can be improved is of great significance for subsequent analysis and understanding of related physical processes in experiments. Based on the wavelet threshold denoising method, the simulated signals and the tungsten atomic spectrum data in tokamak experiment are treated fundamental research subjects, the signal-to-noise ratio (SNR) and root mean square error (RMSE) are used as the judgement basis of the filtering effect. The comparative analysis of simulation experiments shows that when sym5 wavelet base, 4-layer wavelet decomposition, heuristic threshold calculation and progressive semi-soft threshold function are selected for wavelet denoising, the maximum signal-to-noise ratio of 28.2107 and the minimum root mean square error of 0.0082 can be obtained. The as-received approach is used to process the tungsten atomic spectrum, which results show that the wavelet threshold denoising can effectively eliminate the noises in the tungsten atomic spectrum while avoiding signal distortion, that is, a significant improvement of the signal quality.

Key words: spectroscopy, spectral signal of tungsten atom in divertor, wavelet transform, threshold denoising, signal-to-noise ratio, root mean square error