Early tied‐arch bridges cannot satisfy the current traffic load demand due to their load grades and maintenance levels. Also, these tied‐arch bridges have accumulated structural damage with increasingly prominent safety risks. In order to accurately evaluate the characteristics of tied‐arch bridges’ structural‐influenced lines and identify damage of their arch ribs and suspenders, two analytical solutions are derived and established in this paper for the thrust‐influenced lines of parabola and catenary two‐hinged arches with a tie beam. A new method and an index for identifying damage of arch ribs and suspenders of tied‐arch bridges are proposed. The results of numerical simulation in this paper verified that the proposed analytical solution has good analytical accuracy in practice on those two‐hinged nonflat arches. With the use of equivalent thrust‐influenced line difference curvature, the effectiveness of damage identification and the verification method were verified on the tie beam, suspender, and arch rib of plane tie arch structure as well as the suspender and arch rib of tied‐arch bridges in this research. Furthermore, combining with grey relation analysis, the noise immunity of the proposed index method can be verified. Also, thrust‐influenced line recognition based on VMD (variational mode decomposition) is introduced, and a practical process of bridge health assessment based on the quasistatic‐influenced line loading of three‐axle heavy vehicles is established. Theoretical analysis and numerical verification show that the calculated error of the analytic solution of two‐hinged arches with a rise‐span ratio greater than 1/8 is less than 9.57%, and the error decreases with the increase of the rise‐span ratio. Therefore, it can be applied to the calculation and analysis of tied‐arch bridges with a rise‐span ratio range between 1/4 and 1/5. With the equivalent thrust‐influenced line index proposed in this paper, the damage of suspenders and arch ribs of tied‐arch bridges can be accurately located. It has been found that the proposed method is more effective to identify the damage of suspenders than the damage of arch ribs does, showing good noise immunity. In summary, this research has provided theoretical support for arch bridge design and evaluation. Combining with existing bridge‐monitoring methods, the new bridge damage identification method proposed in this paper has the prospect of realizing the normal health status assessment of existing tied‐arch bridges.

Generally, the damage of the structure will lead to the discontinuity of the local mode shape, which can be well reflected by the modal curvature of the structure, and the local information entropy of the beam structure will also change with the discontinuity of the mode. In this paper, based on the information entropy theory and combining the advantages of modal curvature index in damage identification of beam structure, the modal curvature utility information entropy index is proposed. The modal curvature curves of nondestructive structures were obtained by fitting the modal curvature curves of damage structures with the gapped smoothing technique to avoid dependence on the baseline data of nondestructive structures. The index comprehensively reflects the damage state of the structure by calculating mutual weight change matrix and the weight‐probability coefficient. The performance of the new index was verified by the finite element simulation and model test of simply supported beam, respectively. The results show that the modal curvature utility information entropy index takes advantage of the modal curvature index which is sensitive to damage and can overcome its shortcomings effectively. The index proposed can identify the damage location and damage degree accurately and has certain noise immunity, which provides an effective damage identification indicator for beam structures.

There is no analytical solution to the deflection influence line of catenary hingeless arches nor an explicit solution to the deflection influence line difference curvature of variable section hingeless arches. Based on the force method equation, a deflection influence line analytical solution at any location before and after structural damage is obtained, and then an explicit solution of the deflection influence line difference curvature of the structural damage is obtained. The indexes suitable for arch structure damage identification are presented. Based on analytical theory and a finite element model, the feasibility of identifying damage at a single location and multiple locations of an arch bridge is verified. This research shows that when a moving load acts on a damaged area of an arch structure, the curvature of the deflection influence line difference will mutate, which proves theoretically that the deflection influence line difference curvature can be used for the damage identification of hingeless arch structures. This research has provided theoretical support for hingeless arch bridge design and evaluation. Combined with existing bridge monitoring methods, the new bridge damage identification method proposed in this paper has the potential to realize normal health status assessments of existing arch bridges in the future.

For the simple bridge structure, the finite element model established by drawing and elastic mechanics method is accurate. However, when faced with large and complex long-span bridge structures, there are inevitable differences between the finite element model and the physical model, where the model has to be updated. It is problematic that the updating structural matrix cannot be fed back into the existing general finite element calculation software in the traditional structural matrix updating method. In this paper, a parameter-type updating method based on the “Kriging model + swarm intelligence” optimization is proposed. The Kriging model, based on Genetic Algorithm (GA), Bird Mating Optimizer (BMO), and Particle Swarm Optimization algorithm (PSO), is introduced into the finite element model, updating this to correct the design parameters of the finite element model. Firstly, a truss structure was used to verify the effectiveness of the proposed optimization method, and then a cable-stayed bridge was taken as an example. Three methods were used to update the finite element model of the bridge, and the results of the three optimization algorithms were compared and analyzed. The results show that, compared with the other two methods, the GA-based model updating method has the least time due to the small computation. The results of the BMO-based model were time consuming compared to the other two algorithms, and the parameter identification results were better than the GA algorithm. The PSO algorithm-based model updating method to solve the finite element model was repeated, which required a large amount of computation and was more time consuming; however, it had the highest parameter correction accuracy.

Concrete simply supported beams are widely used in small‐ and medium‐sized bridges. Hinged slabs and joints are damaged in service easily, as they are the main load‐carrying members of bridge. In this paper, using the high sensitivity and strong antinoise characteristics of strain energy to damage, a strain energy information entropy index is proposed for identifying local damage in hinge joints and hinged slabs. Moreover, a new damage index of the local strain energy entropy function is constructed according to the strain energy of a hinge joint element and its surrounding elements. A simply supported beam model is established to verify the effectiveness of the proposed index. The numerical simulation results show that the proposed damage index of hinge joints can accurately locate and quantify the degree of damage of single‐hinge joints and multihinge joints. The improved modal strain energy information entropy index is sensitive to single‐hinge slab damage and can accurately identify damage with noise levels of 5% and 10%.