[PERSON] et al. [14] combined DTs and virtual reality technology to propose an intelligent control method for underground equipment, which solved the problem of difficulty in remotely controlling cantilevered road heading machines. [PERSON] et al. [15] proposed an intelligent regulation and control system for air flow at the outlet of the digging face by analyzing the DT technology, thereby realizing the mapping interaction between the physical entity and the virtual twin in the coal mining process. [PERSON] et al. [16] used DT technology in vehicle life prediction and maintenance decision making, which describes the working state of the system more accurately, thus enabling online optimal decision making and feedback control of the vehicle. [PERSON] et al. [17] proposed an integrated maintenance decision model for cranes under operating conditions based on the DT concept, which effectively improved the operational efficiency of cranes and reduced the safety risk of equipment operation. [PERSON] et al. [18] proposed a DT model of a centrifugal impeller and established parametric centrifugal impeller DTs, which can significantly improve the design and manufacturing level of the centrifugal impeller and shorten the design cycle. [PERSON] et al. [19] proposed a DT framework for solving the health state monitoring problem of complex systems, which improves the accuracy and reduces the uncertainty of analysis for the health monitoring of complex systems in intelligent manufacturing. [PERSON] et al. [20] used the DT concept for the detection of electric drive faults, which improved the performance analysis accuracy of electric vehicles during usage. [PERSON] et al. [21] conducted a study to accurately analyze the structural integrity and remaining service life of aircraft. Based on the study of high-fidelity nondestructive inspection techniques, a DT of the structure was created to optimize the monitoring mechanism, which provided a reference for the performance analysis of complex structures. This shows that DT technology has been studied and widely applied in manufacturing. Owing to the lack of research on the assessment of structural safety performance during tensioning of prestressed steel structures and combined with the status of research on DTs, this paper proposes an intelligent discrimination method based on DTs for the sensitivity analysis of mechanical parameters of prestressed cables. The safety performance of the structure is intelligently evaluated through the analysis of the sensitivity of the component mechanical parameters. First, based on the concept of DTs, a framework for sensitivity discrimination was established, and the real tension was dynamically perceived and simulated. In the virtual model, the mechanical parameters of the structure can be extracted directly, and the mechanical properties of the structure can be displayed intelligently. After extracting the mechanical parameters, the Dempster-Shafer (D-S) evidence theory was fused to process the structural mechanical performance information. Therefore, the change probability of the mechanical parameters of each node of the cable was accurately analyzed, and the sensitivity of the prestressed cable was intelligently determined, thus providing a basis for the safety performance evaluation of the structure. Driven by DTs, the D-S evidence theory is integrated to realize intelligent discrimination of the sensitivity of the mechanical parameters of the prestressed cable. Based on the above theoretical method, application was made to a wheel-spoke cable truss as an example. In this study, the sensitivity of the mechanical parameters of the cable under the effect of temperature during tensioning was analyzed, and the effectiveness of this method was verified.