Research on the structural performance monitoring system of bucket wheel under the digital twin technology

Abstract

The bucket wheel reclaimer, critical for large-scale coal yards, faces challenges from its massive structure, complex components, and variable working conditions, leading to performance degradation and failure risks. This paper proposes a structural performance monitoring method using digital twin technology. Discrete finite element analysis (FEA) results are transformed into a dynamic numerical model for real-time stress calculations. By linking FEA mesh data with computer graphics, the geometric model is reconstructed, and stress results are mapped as cloud plots for real-time monitoring. A case study on the pitch mechanism validates the system during a multi-layer sloped cutting process. Simulations show that maximum predicted stress values have a mean absolute error (MAE) under 3 MPa compared to FEA, with an average update interval of 0.27 s, meeting the 1-s delay requirement of the Digital Twin Maturity Model L3. This approach enhances real-time structural performance prediction, offering new insights into intelligent bucket wheel reclaimer management.