Research on Early Warning of Hoist Failure based on Big Data and Parallel Simulation

Abstract

Abstract Aiming at the problems of easy fault diagnosis and difficult early warning of mine hoist, a parallel system architecture of hoist fault early warning based on big data is proposed, the structure of each subsystem of hoist is analyzed, and a parallel simulation system of hoist fault early warning is established; secondly, the Hadoop ecosystem of hoist is established on the virtual machine, and the massive data is mined by using clustering algorithm and association rule algorithm, so as to speed up the calculation speed and improve the reliability of early warning; finally, the safety state evaluation rules of hoist are proposed, and the system decision is made according to the fault early warning results. The experimental results show that it can achieve the purpose of fault prediction.