Surface Inspection of Carry Side of Coal Conveyor Belts using Open CV and Machine Vision Algorithms

In the Mining Industry, Conveyors are extensively used to carry various raw materials,coal and fluxes from remote mine faces to the stock yards/processing plants and other upstream process. These conveyors made of rubber or steel corded rubbers are extremely critical for plant operations and any breaks in the belts can require several days for repair. An early warning system is being devised to detect surface erosions, abrasion and tears in their nascent stages so that by splicing or vulcanization repairs can be effected immediately and life of the belt can be extended .This paper presents an efficient method to use Open CV algorithms on appropriately illuminated images from an area scan camera or any high resolution cameras to contrast, texturize and detect various categories of defects. Experimental evaluation shows that for a standard severity index Gaussian and Laplacian operations provide the desired results and least false positives among all techniques evaluated. The system software then facilitates manual defect categorization and classification for subsequent Automatic Defect Detection.