For the static loading test, digital twin (DT) constructed by multi-type data fusion can combine the advantages of these data, which has potential application in test monitoring. Affected by assembly and manufacturing defects of test system, the loading deviations are difficult to avoid and quantify, and it has an important effect on the strain state of structures. However, the current DT is built by data fusion of strain gauges data and strain field of finite element analysis (FEA) only, and how to build DT considering real-time loading deviations by fusing multi-type sensor data remains a challenging task. Therefore, a strain field reconstruction method based on DT considering the real-time loading deviations (DT-SFRM-LD) is proposed to improve the accuracy of DT. In the test, the loading deviations calculated by displacement sensors data are used as FEA database input to obtain FEA strain field considering real-time loading deviations. The FEA strain field is combined with strain gauges data to construct DT in real time, which combines all the multi-type data advantages of displacement gauges, FEA strain field and strain gauges. A cylindrical shell test is performed to validate the high accuracy of DT-SFRM-LD. Results indicate that the AvgErr (5.0%) and MaxErr (13.6%) of DT-SFRM-LD are 4.3% and 10.0% lower than those of conventional DT method, and the AvgErr of DT-SFRM-LD is less affected by the eccentricity distance. In general, under different test conditions, the accuracy of DT-SFRM-LD is always higher than that of conventional DT method, indicating that considering the real-time loading deviations by displacement gauges is helpful to provide accurate FEA strain field distribution and to improve the accuracy of DT-SFRM-LD.
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