Advanced real-time data quality monitoring model for tokamak plasma diagnostics

Modern physics experiments require construction of advanced, modular measurement systems for data processing and registration purposes. The most important systems are connected to the feedback loop in order to perform real-time experiment control. The paper is related to soft X-ray measurement systems working on tokamaks. As the sensor unit the GEM detector is considered. The hardware platform consists of analog and digital data path, with data preprocessing in FPGAs and real-time output products computation in embedded PC (CPU). The main focus in put on the importance of output products data quality from the measurement systems. In the paper is presented the model of the data evaluation and quality monitoring component for work in real-time. The typical hardware and data path structure is described, with analysis of the low-quality data propagation, in order to present the most optimal placement of the DQM data filtering structure. The DQM model is divided into the FPGA and CPU part. The model is based on iterative signal classification unit working in real-time. Additional sub-diagnostics allows recording and analysis of the events in term of raw data and statistical information. In a summary section the benefits from model implementation are described. The presented model is designed in universal, modular approach and can be applied to various measurement systems.

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