Automated Shovel Tooth Wear Monitoring with Machine Vision

CIM Montreal 2011
Shahram Tafazoli, Mehran Motamed,
Abstract Tooth wear on mining shovels presents a challenge for productivity. A shovel with worn teeth suffers from increased digging forces, longer fill times, and an increased likelihood of lost or broken teeth and adapters.
Efficient maintenance planning relies on knowledge of tooth decay rates and patterns. A fully automated wear monitoring system can record detailed logs of tooth wear, permitting G.E.T. personnel to optimize maintenance scheduling. Studies have demonstrated that planned tooth change-outs result in significantly reduced costs as compared to unplanned maintenance.

A machine-vision based tooth-wear monitoring method is introduced. A rugged camera is installed on the boom of cable shovels, such as those made by Bucyrus or P&H, or on the stick of hydraulic shovels such as those by Komatsu or Liebherr. The images are processed using a photogrammetric algorithm to determine the individual tooth lengths. Tooth length data is collected at intervals during shovel operations, forming a profile of the current wear state and speed of decay, wear pattern, and expected lifespan of teeth.

Armed with this kind of data, mine personnel can reduce the cost and lost time due to unplanned maintenance, and observe the effects of mine conditions and operator behaviour on tooth wear.
Keywords: Automated monitoring, Maintenance management, Maintenance Planning, Shovel Tooth Wear, Wear Monitoring, machine vision, Ground Engaging Tools, Maintenance Planning, Tooth Wear
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