The increasing demands on the reliability and efficiency of agricultural machinery make the task of studying the wear of working members more and more urgent. A review of the possibilities of machine vision technologies for analyzing the wear of structural elements of tillage machinery is presented. Key approaches such as 3D surface reconstruction, image processing and the use of deep learning methods have been considered. The prospects of automating the assessment of the condition of parts, eliminating the subjective factor in diagnostics and improving the accuracy of measurements were analyzed. Special attention was paid to the technological capabilities of machine vision, its advantages over traditional analysis methods and potential areas for further research in the field of increasing the service life of working members of tillage machines.
Кравченко et al. (Wed,) studied this question.
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