Data Quality Monitoring Considerations for Implementation in High Performance Raw Signal Processing Real-time Systems with Use in Tokamak Facilities

Data quality of the tokamaks diagnostics is often a neglected topic. In literature it is rather rare to find considerations regarding the data quality received from the diagnostic systems’ sensors. The scope of the paper is to provide a discussion regarding systems’ construction and analysis in scope of implementation of data quality monitoring methods for a new generation of diagnostics. Mainly considerations are performed regarding the necessity of DQM (Data Quality Monitoring) implementation, functionality, performance and required system resources. The covered topics are related to basics of system construction including: system layout and construction blocks, data processing stages, signal processing modes, system construction with resource estimation in scope of DQM implementation. Based on the covered points, it is possible to plan the extra resources or specific construction, to provide reliable design with data quality monitoring features. The data quality monitoring aspect is especially important in the modern diagnostics working with a real-time feedback loop. Such approach could be especially interesting for the ITER-like projects, since the quality of the data may directly influence the behavior of the control systems during plasma phenomena. The work is based on experience in design work of various high performance diagnostic systems for plasma physics and high energy physics.

The cluster charge identification in the GEM detector for fusion plasma imaging by soft X-ray diagnostics

The measurement system based on gas electron multiplier detector is developed for soft X-ray diagnostics of tokamak plasmas. The multi-channel setup is designed for estimation of the energy and the position distribution of an X-ray source. The focal measuring issue is the charge cluster identification by its value and position estimation. The fast and accurate mode of the serial data acquisition is applied for the dynamic plasma diagnostics. The charge clusters are counted in the space determined by 2D position, charge value, and time intervals. Radiation source characteristics are presented by histograms for a selected range of position, time intervals, and cluster charge values corresponding to the energy spectra.