Sensor-based inspection system developed for conveyors17 December 2020
Technology company Continental has developed a digital AI-based monitoring solution for conveyor-belt systems which is designed to allow predictive maintenance and weak-point identification before damage occurs.
Sensor-based technologies are used to replace what would otherwise be laborious manual inspections. Using cameras and acoustic signals, the system is designed to detect idler defects and allow data-assisted planning of maintenance intervals.
A typical conveyor in tunnelling could have hundreds, if not thousands, of belt idlers. The new technology aims to address the fact that around 30% percent of operational faults with belt conveyors are attributable to idler defects that could not be identified in a timely manner.
Continuous maintenance in underground conveyors would be carried out using fixed microphones installed every 20-25m which capture frequency variations in the numerous idlers. The audio recording is conducted twice a day, with the data uploaded to the cloud. Events that indicate a damaged idler are then investigated using an AI-based algorithm. Sections of conveyor in the open air would be monitored by a drone quipped with infrared and RGB cameras.
Continental’s solution has been successfully tested in initial field trials. Further pilot projects with potentially interested parties are planned. The system is scheduled to be operational in the course of 2021.