Bridge damage localization and quantification using deep learning and FEM static simulation

Among the existing unsupervised bridge damage detection methods, it is difficult to quantify bridge damage severity levels, although some of the methods can achieve the localization of bridge damage. In the existing research, the damage index (DI) curve is calculated by the monitoring point dynamic response (inclination or deflection) of the bridge in the damage state, and the localization of the bridge damage can be achieved by the DI curve without the need for damage labels. Based on this bridge damage localization method, this paper proposes an efficient bridge damage severity level quantification method. Since the different DI curves calculated under the same damaged state basically coincide with each other, the DI curves will change with the bridge-damaged state. Therefore, the quantification of the bridge damage severity level is achieved by only calculating DI curves of different damage degrees at the damage location. To efficiently calculate the DI curve, this paper proposes a method for generating the monitoring point dynamic response of the specified damage bridge. By the specified damage bridge finite element model (FEM) static simulation to obtain arbitrary vertical nodal loads and monitoring point responses of the relationship function, and then combined with the healthy state of the bridge monitoring point dynamic response can be generated monitoring point dynamic response of the specified damage bridge. Since the method in this paper is based on real measured data to calculate the DI curve, it is more robust to noise and modeling errors than the FEM dynamic simulation method, and the modeling of this method only needs to update the model stiffness parameter to reduce the modeling cost. In the example of this paper, the method of this paper calculates the DI curve of one damage state only needs about 7 s about 437 times the computational efficiency of the FEM dynamic simulation method, which can achieve the fast quantification of bridge damage severity levels. Numerical simulations demonstrate that the method can localize and quantify multi-damage in bridges under unknown loads, a small number of sensors, noise, and modeling errors. However, the method in this paper still has limitations that do not apply to the localization and quantification of bridge pier damage and nonlinear models.