Poster + Paper
20 May 2022 Algorithm for the automated determination of the forms to electrical discharge processes used to analyze the formed electrolyte plasma and predict the properties of the formed metal oxide layers
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Conference Poster
Abstract
Analysis of technological and chemical processes in difficult and hazardous conditions for humans, with the release of a large amount of energy or the formation of harmful compounds, requires automated control. The article proposes an algorithm for the automated analysis of the forms of arcing, shapes and areas of contact of electric discharges with the surface of an object. The need for automation is associated with forming large amounts of data related to the high-speed shooting of even one process. To analyze the areas of contact of an arc discharge with the surface of an object, the work uses a technique that includes the following main stages: Pre-processing of data, including the task of noise reduction, elimination of impulse bursts, contouring of objects, elimination of blur and increasing the distinguishability of contact areas; Post-processing of data, including the task of analyzing objects, excluding objects of small shapes from consideration, exploring interframe intersections, combining shapes and forming areas of intensities. At the final stage, the correspondence of the ratio of the obtained areas of electric-discharge contact with the intensity of the emitted and recorded voltage is given. On a set of test data of the processes of formation of surface layers during the electro-plasma formation of metal oxide layers fixed by a low-resolution high-speed camera, we show the results of applying the proposed method, the dependence, and shape of points of contact, and their relationship with the resulting properties of the created coatings are shown.
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Aleksandr Zelensky, Sergey Zhukov, Olga Zhukova, Marina Zdanova, Viacheslav Voronin, and Evgenii Semenishchev "Algorithm for the automated determination of the forms to electrical discharge processes used to analyze the formed electrolyte plasma and predict the properties of the formed metal oxide layers", Proc. SPIE 12136, Unconventional Optical Imaging III, 1213619 (20 May 2022); https://doi.org/10.1117/12.2625837
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KEYWORDS
Oxides

Metals

Plasma

Image processing

Feature extraction

Visual analytics

Statistical analysis

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