Abstract
Worn surfaces of the chute linings used under impact and sliding contact conditions in an iron ore plant were characterized. A new method for wear surface analysis of chute linings supported by computer vision tools was developed. The created machine learning model not only recognized and classified wear mechanisms but also mapped and estimated their corresponding affected areas on the entire working surface of the sliding contact lining. A combination of impact and abrasion wear modes took place for the impact contact lining, while LSSA and corrosion wear modes were identified as acting simultaneously on the sliding contact lining.
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