A Digital Twin Monitoring System for Belt Conveyor

Regular manual inspection is the main maintenance method of belt conveyors. The method has problems such as low efficiency and poor accuracy. In addition, complex structures and operating scenarios require corresponding multi-disciplinary equipment models that accurately reflect real-time state changes. In this study, a digital twin system architecture for equipment monitoring is proposed. The multi-source sensors, 5G technology, and digital twin modeling are applied on the construction of different layers, and the corresponding frameworks are proposed. The architecture was applied in a belt conveyor and significantly improved the intelligent level of health monitoring. It can provide a useful reference for systems with similar requirements.