Abstract
In the work, the problem of automated classification of tribochemical damage of metallic surfaces based on digital image processing was considered. Five types of tribochemical wear damage, including fretting, smearing damage, combinations of oxidation and erosion wear, and wear in corrosive media were investigated. Initial images were characterized by a set of texture features. The effectiveness of using the developed method for automated identification of tribochemical surface damage types was demonstrated.
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