关键词: 小波变换, EAST, 偏滤器光谱信号, Stark展宽, 电子密度

Abstract: To improve the accuracy of the calculation of plasma electron density by Stark broadening, based on the wavelet threshold denoising processing method for EAST divertor deuterium spectral signals and using the signal-to-noise ratio (SNR) and root mean square error (RMSE) as the evaluation basis for the filtering effect, the optimal wavelet basis db4 is determined by comparison, and the optimal wavelet decomposition is 4 layers. The adaptive threshold parameter is calculated according to the noise estimation to reconstruct the signal, and the denoised data is applied to the analysis process of the plasma density calculated by the Stark broadening algorithm. The results show that the wavelet hard threshold denoising can effectively improve the signal-to-noise ratio of the spectral signal, reduce the root mean square error, and eliminate the noise in the spectral signal while retaining the useful spectral detail feature information to the greatest extent, which is beneficial to the spectral data modeling effect, and the more accurate plasma electron density is obtained.  

Key words: Wavelet transform, EAST, Divertor spectral signal, Stark broadening, Electron density