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This study aims to correlate the vibration data with quantitative indicators of structural health by comparing and validating the feasibility of identifying unknown excitation forces using output vibration responses. First, numerical analysis was performed to investigate the accuracy, convergence, and robustness of the load identification results for different noise levels, sensors numbers, and initial estimates of structural parameters. Then, the laboratory beam structure experiments were conducted. The results show that using the two identification methods Tikhonov (L-curve) and TSVD (GCV-curve) can successfully and accurately identify the different excitation forces of the external hammer. The TSVD based on GCV method has more advantages than the Tikhonov based on L-curve method. The proposed two kinds of load identification procedure based on vibration response can be applied to the safety performance evaluation of the railway track structure in future inverse problems research.

Landslide induced by rainfall is very common in the world, which seriously threatens the safety and construction. Taking the landslide on the right bank of the Xiajiang Water Control Project as an example, this paper carried out comprehensive monitoring of groundwater level, earth pressure, and surface deformation of the landslide analyzed the landslide formation mechanism and predicted the stability of the landslide. The results show that the rainfall infiltration caused fluctuations in the groundwater level of the slope, which caused the instability of liquefaction in the shallow surface layer, fluctuations in the reservoir reduced the stability of the slope. Groundwater activity between the bedrock and the soil-rock mixture controls the slope stability to a large extent. Based on the comprehensive impact analysis of these triggering events, it is considered that the slope is undergoing continuous deformation and needs to be landslide management.

An improved load identification technology of a beam based on different regularization methods and model modifying methods is presented in an attempt to minimize the estimation error at several periodic loads. A hybrid model is developed to simulate such ill-posed problem interactions under different noise levels. The finite element model is modified with the different optimization algorithms to obtain the equivalent constraint condition. Experimental verification is also carried out to obtain correct modes and frequencies by considered vibration response and different boundary conditions. The measured results demonstrate the good agreement with the identification results. The results are shown that the improved method not only has more adaptive range and higher identification accuracy but also has effective identification ability for loads under different noise levels.