INTELLIGENT SYSTEM FOR THE TWO-PHASE FLOWS DIAGNOSIS AND CONTROL ON THE BASIS OF RAW 3D ECT DATA
In this paper the new intelligent system for two-phase flows diagnosis and control is presented. The authors developed a fuzzy inference system for two phase flows recognition based on the raw 3D ECT data statistical analysis and fuzzy classification which identify the flow structure in real-time mode. The non-invasive three-dimensional monitoring is possible to conduct even in non-transparent and non-accessible parts of the pipeline. Presented system is also equipped with the two phase gas-liquid flows installation control module based on fuzzy inference which includes the feedback information from the recognition module. The intelligent control module working in a feed-back loop keep the sets of required flow regime. Presented in this paper fuzzy algorithms allow to recognize the two phase processes similar to the human expert and to control the process in the same, very intuitively way. Using of the artificial intelligence in the industrial applications allows to avoid any random errors as well as breakdowns and human mistakes suffer from lack of objectivity. An additional feature of the system is a universal multi-touched monitoring-control panel which is an alternative for commercial solution and gives the opportunity to build user own virtual model of the flow rig to efficiently monitor and control the process.
fuzzy inference; fuzzy logic; fuzzy control; 3D capacitance tomography; raw measurement data analysis; fluid flow measurement and control
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