Research on Fault Diagnosis and Early Warning of Mining Belt Conveyor Drive Device Based on AI Technology
ZHANG Shuo
Abstract：A fault diagnosis and warning system for the driving device of mining belt conveyors based on AI intelligent expert algorithm was proposed to address the issues of high labor intensity,low accuracy,small coverage,and single monitoring methods used in traditional manual maintenance methods for the driving device of mining belt conveyors.Through AI identification and analysis,the driving device gear misalignment,movement,eccentricity,wear and movement were identified and analyzed.The gear meshing frequency(GMF)features of abnormal working conditions such as broken or broken teeth in gear combinations,after learning and training,were ultimately built into a GMF feature expert library.The experiment showed that the fault diagnosis platform combining AI technology and feature expert library had a recognition rate of 92.3％,an accuracy rate of 90.4％,and a response time of 29 ms.High accuracy and fast response time can avoid equipment fault accumulation leading to accidents,greatly improving the fault diagnosis efficiency of various components of the belt conveyor,and effectively ensuring the safety of underground transportation in coal mines.
Keywords：mining belt conveyorfault diagnosis and early warningAI technology
Publication Date：2023-10-12
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 59-63 )