Metal magnetic memory testing (MMMT) is a nondestructive testing technique that can detect early signs of damage in components. Many scholars have studied the effect of uniaxial stress on the self-magnetic-leakage field (SMLF)’s strength. Nevertheless, there is still insufficient research on the combined action of bending and shear. We studied the law of distribution of the magnetic signal,$\Delta H_{\mathrm{SF}}\left(\mathrm{y}\right)$, at different stress parts of a steel box girder and the quantitative relationship between the magnetic characteristic parameters and the external load. The results showed that the MMMT could accurately detect the early stress concentration zone (SCZ) and predict the final buckling zone of steel box girders. It could be judged that the corresponding parts of the steel box girder had entered the elastic-plastic working stage by the reverse change of the $\Delta H_{\mathrm{SF}}\left(\mathrm{y}\right)$-F and${\left|H_{\mathrm{SF}}\left(\mathrm{y}\right)\right|}_{a }$-F curve trends, this feature could be used as an early warning sign before the steel box girder was deformed or destroyed. The fitted${\left|H_{\mathrm{SF}}\left(\mathrm{y}\right)\right|}_{ave }$-F linear expression could be used as the expression between the magnetic signal and the shear capacity. All the evaluation methods were expected to provide a basis for effectively evaluating the stress state of steel box girders with the MMMT method.

It is valuable to conduct non-destructive testing of steel box girders in order to evaluate their working status. The metal magnetic memory inspection method can effectively identify early damage and the stress state of ferromagnetic materials. However, applying this technique in the inspection of steel components is difficult due to insufficient research on magnetic memory signals under complex stress states. This study analyses the magnetic memory effect for a steel box girder under four-point bending. It is shown that the normal component H_p(y) of the magnetic signal can effectively locate the stress concentration area. The average absolute value H_m of H_p(y) can identify the yielding state and predict the occurrence of failure. H_m changes roughly quadratically with the average strain ɛ_m in the elastic stage of the specimen, which is consistent with the theoretical result. The ratio D of H_m to the equivalent stress σ_eqv changes continuously with the applied load, which can be used to estimate the stress state of the steel box girder.

Given the critical role of steel bridges in transportation infrastructure, conducting nondestructive testing is essential for ensuring their operational safety. The metal magnetic memory (MMM) technique provides an effective method for assessing stress in steel bridges. To address this, MMM testing was conducted on Q345qD bridge steel specimens subjected to tensile loading-unloading stress. Magnetic signals were acquired and we achieved the stress evaluation considering detection orientation using the average value A_y of the tangential magnetic field component H_my and the linear fitting slope K_z of the normal component H_mz, yielding a maximum error of 6.68%. We further proposed a force-magnetic coupled finite element analysis approach applicable to evaluate the stress in bridge steel, which can account for the loading history. The initial boundary conditions for the finite element analysis of the magnetic field were determined based on experimental data, specifically defining the magnetic scalar potential and the component of the effective external magnetic field co-axial with the applied stress. It is expected to enhance the reliability of MMM technology for stress assessment in bridge steel.