Feasibility Study of Neural Network-based Classification of Conveyor Belt Damage Using Partial DiagBelt Data - Rzeszowska, Aleksandra; Jurdziak, Leszek; Błażej, Ryszard (Zielona Góra: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego)
Non-invasive methods for diagnosing conveyor belts enable effective detection of damage, significantly reducing the costs associated with belt replacement. Additionally, they allow for continuous monitoring of the belts` technical condition and degree of wear over extended periods of operation. Such solutions also enhance safety in environments where conveyor systems are used. While belt wear is an inevitable process, its rate can vary depending on specific operational conditions, such as the conveyor`s location, its length, the type of material being transported, and the belt`s operating speed.
Keywords: conveyor belt; magnetic method; DiagBelt system; damage detection; artificial neural networks