Damage identification is a key problem in the field of structural health monitoring, which is of great significance to improve the reliability and safety of engineering structures. In the past, the structural strain damage identification method based on specific damage index needs the designer to have rich experience and background knowledge, and the designed damage index is hard to apply to different structures. In this paper, a U-shaped efficient structural strain damage identification network SDFormer (structural damage transformer) based on self-attention feature is proposed. SDFormer regards the problem of structural strain damage identification as an image segmentation problem, and introduces advanced image segmentation technology for structural damage identification. This network takes the strain field map of the structure as the input, and then outputs the predicted damage location and level. In the SDFormer, the low-level and high-level features are smoothly fused by skip connection, and the self-attention module is used to obtain damage feature information, to effectively improve the performance of the model. SDFormer can directly construct the mapping between strain field map and damage distribution without complex damage index design. While ensuring the accuracy, it improves the identification efficiency. The effectiveness and accuracy of the model are verified by numerical experiments, and the performance of an advanced convolutional neural network is compared. The results show that SDFormer has better performance than the advanced convolutional neural network. Further, an anti-noise experiment is designed to verify the anti-noise and robustness of the model. The anti-noise performance of SDFormer is better than that of the comparison model in the anti-noise experimental results, which proves that the model has good anti-noise and robustness.

This paper proposes a variable stiffness collision post (VSCP) structure based on a uniform stiffness collision post (USCP) structure and performs stiffness matching optimization for VSCPs. A collision post structure assembled in a subway front-end frame can maintain the living space and absorb a certain amount of the kinetic energy of an impact. The experiment was applied on USCP, and the finite element model was verified experimentally. To investigate the effects of the stiffness parameters of VSCP on the specific energy absorption response (SEA_VSCP) and the area of intrusion response (S_In), response surface models fitted from design of experiment were adopted with the finite element model. In addition, a multiobjective optimization design was realized by using the global response search method and a Pareto frontier sequence was generated, which was based on the developed response surface model. It was found that the optimal value of SEA_VSCP and S_In responses cannot be achieved at the same time. Finally, a grey relational analysis is propounded to attain a desirable balance between SEA_VSCP and S_In from the Pareto frontier sequence under constraints of the peak crash force of VSCP and energy absorption of the front-end of cab car. The optimization result shows that the crashworthiness of VSCP is better than that of USCP.

For the complex operating environment of rail vehicles impacted by foreign objects, this study carried out experiments on carbon fiber composite laminates impacted by projectiles of three different materials in the gas gun apparatus. High-speed photography was used to capture the impact dynamic process, with subsequent analysis of image sequences enabling the quantification of both projectile energy characteristics and laminate mechanical responses. The key findings reveal that (1) the impact force demonstrates a nonlinear relationship with the energy input, exhibiting diminishing growth rates at higher energy levels, while deformable aluminum projectiles yield significantly lower average impact forces; (2) crack propagation follows a characteristic pattern of initial expansion with the impact energy reaching maxima of 88.40 mm (concrete), 41.48 mm (steel), and 80.35 mm (aluminum), and then decreasing, followed by stabilization post-perforation; (3) the penetration depth showed an accelerating nonlinear growth trend with progressively higher rates of increases as the impact energy rose, and its variation trend exhibited a correlation with the crack length. The results provide quantitative insights into carbon fiber laminates’ damage mechanisms, which offer practical implications for the composite structure design in transportation systems subjected to foreign object impacts.