Research on Predictive Maintenance Methods of Shearer Hydraulic System Based on Digital Twin

Abstract

With the continuous improvement of intelligent level and measurement and control level in mines, higher requirements are put forward for the effective maintenance of mining equipments. In this paper, a study has been made of the condition monitoring, fault prediction and predictive maintenance scheme of coal mining equipments. Taking the shearer as the research object, this paper analyzes the common faults and characteristics of the hydraulic system of the shearer, formulates the construction scheme of the digital twin body of the hydraulic system of the shearer, clarifies the mechanism and implementation process of the predictive maintenance system, puts forward the condition monitoring and fault prediction method based on the hydraulic state signal, with the digital twin body of the hydraulic system of the shearer constructed, thus the predictive maintenance system is designed based on MR (mixed reality), which ensures the safe and stable operation of the shearer. The system has been experimentally verified for the functions of condition monitoring, fault prediction and predictive maintenance, and the results show that all modules achieve the expected functions.