Semi-autonomous inspection of a belt conveyor in an industrial environment with the use of a legged robot APCOM 2021

In this paper the authors present a walking robot dedicated to the inspection of a belt conveyor’s transportation system in an underground mine. The developed robot can independently diagnose all of the key rotating elements of the belt conveyor (pulleys, bearings, drums, gears, engines) based on vibration and acoustic signals as well as typical RGB (red, green, blue) and thermal images. The article presents key diagnostic procedures applied to real industrial data obtained during robot testing.The work was developed as part of the ‘THING–subTerranean Haptic INvestiGator’ project. The authors presented the main assumptions of the research methodology developed for the needs of technical diagnostics of conveyor elements typical of inspection work performed by mining staff. Based on industrial data, the use of algorithms for elements such as rollers, drive stations, and the conveyor belt were shown. The main assumption of the research is to develop a robot adapted to the conditions of a deep mine, capable of carrying out an autonomous inspection of mining infrastructure. The conducted tests and the developed fault detection algorithms were aimed at preparing the robot for underground tests in the operating conditions of the mine.