Overview of Digital Twins in Mining Equipment

Abstract

Digital twin technology is a real-time simulation skill based on computer models and real physical systems. Digital twin for extractive equipment combines physical equipment with virtual models to achieve comprehensive monitoring, prediction and optimization of extractive equipment and its operational status through data integration, simulation and analysis. The key elements of extractive equipment digital twin include sensor and data acquisition, physical model building, model calibration and validation, data analysis and decision support. By collecting the sensor data of the equipment, Efficacy of virtual environments in developing collaboration strategies between industrial robots and humans including parameters such as temperature, vibration, pressure, etc., and then the corresponding digital twin models can be established. These models can be calibrated and verified based on actual data to ensure their accuracy and reliability. Applications of digital twins for extractive equipment include operational status monitoring and prediction, optimization of operation and maintenance strategies, training and knowledge management. Digital twins can also record equipment operation data and fault information to form a knowledge base for subsequent fault diagnosis and decision-making. The application of digital twin technology for mining equipment can improve the efficiency and reliability of mining equipment, reduce operating costs, and help improve the technical level and training of employees.