FUZZY CLUSTERING OF RAW THREE DIMENSIONAL TOMOGRAPHIC DATA FOR TWO-PHASE FLOWS RECOGNITION

The paper contains a description of the fuzzy clustering method usage for the recognition of two-phase gas-liquid flows. The authors present a detailed description of the obtaining process of three dimensional tomographic data, the so-called raw tomographic data, and new methods of the data collection, interpretation and statistical processing. In addition, the article includes a description of the key issues in the field of fuzzy logic and fuzzy clustering such as the determination of the primary features vector or the fuzzy classifier (FCM) principle of use with a specific type of data used in the study. Justifying the choice of fuzzy clustering authors presented the results of experiments carried out, which confirmed that the fuzzy algorithms are very good matched to the study of phenomena of a very dynamic nature, which, definitely, are the two-phase gas-liquid flows.