Research on Key Technologies for Operation Status Perception and Predictive Maintenance of Fully Mechanized Mining Equipment

In order to solve the problems of delayed status perception, slow fault response and others of equipment in the 5303 working face of Chuangyuan Coal Mine, a set of predictive maintenance technical system deeply integrated with the special working conditions of coal mines is constructed. By deploying edge intelligent nodes with intrinsic safety certification and integrating multi-source sensors, a multi-parameter coupling acquisition of hydraulic - mechanical - electrical is achieved; A multi-model fusion architecture for the degradation characteristics of fully mechanized mining equipment is innovatively proposed, combined with the advantages of random forest, support vector machine, and LSTM network, a model with high adaptive fault identification and remaining life prediction is constructed. The on-site verification shows that the system is better than the traditional scheme in terms of accuracy rate in abnormal early warning, response speed for maintenance, and unplanned shutdown control, etc.