Litcius/Paper detail

Damage Detection Based on 3D Point Cloud Data Processing from Laser Scanning of Conveyor Belt Surface

Paweł Trybała, Jan Blachowski, Ryszard Błażej, Radosław Zimroz

2020Remote Sensing50 citationsDOIOpen Access PDF

Abstract

Usually, substantial part of a mine haulage system is based on belt conveyors. Reliability of such system is significant in terms of mining operation continuity and profitability. Numerous methods for conveyor belt monitoring have been developed, although many of them require physical presence of the monitoring staff in the dangerous environment. In this paper, a remote sensing method for assessing a conveyor belt condition using the Terrestrial Laser Scanner (TLS) system has been described. For this purpose a methodology of semi-automatic processing of point cloud data for obtaining the belt geometry has been developed. The sample data has been collected in a test laboratory and processed with the proposed algorithms. Damaged belt surface areas have been successfully identified and edge defects were investigated. The proposed non-destructive testing methodology has been found to be suitable for monitoring the general condition of the conveyor belt and could be exceptionally successful and cost-effective if combined with an unmanned, robotic inspection system.

Topics & Concepts

Point cloudConveyor beltHaulageLaser scanningBelt conveyorComputer scienceData processingEnhanced Data Rates for GSM EvolutionData acquisitionRemote sensingReliability (semiconductor)Automotive engineeringImage processingReal-time computingMining engineeringComputer visionLaserGeologyMechanical engineeringEngineeringAlgorithmImage (mathematics)Power (physics)Quantum mechanicsOperating systemPhysicsOpticsRope3D Surveying and Cultural HeritageBelt Conveyor Systems EngineeringRemote Sensing and LiDAR Applications