Real‐time prediction method of fatigue life of bridge crane structure based on digital twin

Abstract The comprehensive effect of multiple factors that include the geometric characteristics, load status, service characteristics, and failure mechanism will affect the safety of bridge crane structure. To evaluate the security of the bridge crane structure, the real‐time prediction method of fatigue life of the bridge structure based on digital twin is proposed. The specific type of general bridge crane is selected as the physical entity of the research object, and the information acquisition system is utilized to get the current service status information about the physical entity. On this basis, combined with the historical service information and inherent information of physical entity, the fuzzy database is established. Meanwhile, twin data are formed by the clear quantification of fuzzy information and data processing technology. In accordance with structural characteristic and work cycle process of bridge crane, the analytical models of load, strength, defect, and fatigue life are established, respectively. The multi‐theoretical calculation model is completed by encapsulating the analysis models and transmitting information, and then the main factors affecting the fatigue life of bridge crane structure are determined. With that, the comprehensive evaluation coefficient is calculated by the fuzzy comprehensive evaluation theory. The response relationship between the information data and the fatigue life of bridge crane structure is described by the Kriging surrogate model constructed with experimental design. Real‐time prediction of fatigue life of bridge crane structure is realized in a virtual space to depict the life cycle process. Taking QD20/10 t × 43 m × 12 m general bridge crane as an example, the feasibility and applicability of the proposed method are verified, which provides a strong theoretical basis for dependable service and timely scrapping of cranes.