Automatic impurity spectral line identification algorithm with noise reduction for fusion plasmas

Abstract

Accurate diagnostics of impurity behavior inside the tokamak plasma is essential for long and stable plasma operation and also for machine protection in fusion devices including ITER. In this study, a numerical code for identifying impurity line spectra was developed and assessed by utilizing the ITER-relevant vacuum ultraviolet (VUV) spectroscopic diagnostic system in KSTAR. For real-time analysis of a spectrum, it is necessary to reduce the noise level of the data caused by high neutron and gamma photon fluxes reaching the detector such as a charge-coupled device detector. The code uses a high-order derivative method that distinguishes relatively sharp noises from spectral lines. Tests with synthetic spectra showed successful noise reduction of approximately 90%. In addition, an in-situ wavelength calibration algorithm was developed by using representative carbon emission lines (C III and C IV) as markers that appear during the current ramp-up phase in carbon-walled devices. This algorithm is followed by a matching algorithm that enables the annotation of an ionic state of an impurity on the line peak by referencing the NIST atomic database. From the integrated processing algorithm, simulated VUV spectra were tested and the results showed successful automatic annotation of the spectral lines after noise reduction.