Belt conveyors are one of the most popular methods of material transport in many branches of industry, especially in mining. The average length of mining belt conveyor is about 1000 m. Taking into account that total length of transportation ways in averaged mine can approach several dozen of kilometers and network of several conveyors may cover large area, maintenance of such specific transportation system is very difficult. In this work we propose an automatic multi-channel system for data acquisition and processing for damage detection in belts. Belts with steel cords are considered here, they consist of top and bottom rubber covers and steel cords in between them. Due to many reasons (mainly sharpness of transported materials) covers may be damaged and it may initiate degradation process or straight damages in steel cords. Properties of steel cords are therefore crucial for overall strength of belts, if they are damaged, it may cause catastrophic failure of the whole conveyor. So, monitoring of belts conditions is a crucial issue. We proposed a monitoring system that measure and process data from array of magnetic sensors. The system allows to acquire up to 24 channels of NDT signals and uses automatic algorithms to process them in order to get information about begin of the belt loop, location of joints of particular belt segments and the final location and size of damages related to corrosion or cuts of steel cords inside belts. These techniques will be presented in the paper. Our approach has been validated in a lignite mine for several conveyor belts.
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