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Segmentation of electrical discharge processes based on the image analysis of plasma-electrolyte oxidation

In the process of plasma-electrolytic synthesis, a new physical surface is synthesized, consisting of a metal oxide layer of a modified surface and the synthesis of elements of a set of electrolyte plasma, the nodal sources of the components of which are the components of the electrodes (electrolyte and metal surface). In this regard, the classification of plasma electro-discharge processes based on analyzing optical and electrical sensor data using machine learning methods is an actual task. It can be used for intelligent control algorithms of the sensor layers operations and conduct analytical and quantitative studies of the properties of nodal substances. The paper presents the experimental analysis of video and electrical parameters of the oxygen process, automated processing of the basic features of images of plasma-electrolyte discharges, and a segmentation approach of the electric-discharge machining. This approach can help create microsensor elements and materials and systems for intelligent modeling and launching of electrochemical methods for creating an electrolyte plasma and directed synthesis of substances. To test the performance of the proposed algorithm, the database STANKIN is used.