Analysis of Uncertainty in Conveyor Belt Condition Assessment Using Time-Based Indicators

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Abstract
This study analyzes the impact of the type of transported material (overburden, lignite, mixture) on the rate of core damage accumulation in Type St conveyor belts in open-pit mines. The research was conducted using the DiagBelt+ diagnostic system, which enables the assessment of belt core condition without dismantling the belt. Data were collected from over 100 conveyor belt loops, covering segments of varying lengths, ages, and operational histories. Damage density and area were assessed, and differences were analyzed depending on the material type. The results indicate that belt age and damage density vary significantly with material type, while the Resurs indicator (percentage of expected operating time) shows no clear dependence on the material type. A multiple regression analysis was also performed to predict failure density based on operational variables, such as Age, Resurs results, Loop Length, and Segment Length. The regression model explains approximately 46% of the variability in damage density, indicating the need for further research to improve predictive accuracy. The study emphasizes the importance of using non-destructive diagnostic systems to optimize maintenance planning and enhance conveyor belt reliability.

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