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Service performance evaluation is of great significance to the safety, durability, and reliability of bridge engineering. Over the last decade, structural health monitoring (SHM) systems have been widely used for condition monitoring of cable-stayed bridges, massive monitoring data are measured and stored by the sensing subsystems, which provides the basis for service performance evaluation of bridge engineering. Meanwhile, the load test is a common method to assess the construction and service performance of bridges. Combined the SHM systems and a load test of a thousand-meter level cable-stayed bridge after ten years of service, this paper investigates the operating conditions of main structures, including bridge towers, main girders, and steel cables. 52 trucks were used to conduct a quasi-static load on three key sections of bridges. Meanwhile, the GPS displacement of towers and main girders, stress of the main girders and acceleration responses of cables were measured synchronously by the SHM systems. Based on the health monitoring data, the dynamic responses, structural deformation, and cable tension of the bridge were investigated and evaluated by comparing with the finite element (FE) model load test at construction stage. The results show that the service performance of the bridge is basically within the designed conditions.

Fatigue damage in engineering structures is universal. The occurrence of fatigue cracks brings unpredictable hidden dangers to a structure in terms of safety and service performance. Traditional damage identification methods, such as power spectrum analysis, are mostly based on linear elasticity theory that cannot reflect the typical nonlinear characteristics of fatigue cracks and cannot meet the higher requirements of the signal analysis method put forward by current mass detection data. To solve this problem, a numerical model of a cantilever beam with a breathing crack is established in this study. A method for diagnosing fatigue damage is studied by combining bispectral analysis and a statistical normal cloud model, which characterize the nonlinear characteristics of the structure. This method can effectively describe the nonlinear characteristics of the structure and reasonably evaluate the degree of fatigue damage in the structure. The bispectrum-normal cloud model method proposed in this study overcomes the limitations of existing linear damage detection methods in nonlinear damage detection, and can improve the efficiency of signal analysis from a statistical point of view. It has good prospects for structural nonlinear damage assessment.

Fatigue damage is a type of damage usually occurring to repeatedly loaded elements of structures in various engineering fields. Accumulation of fatigue damage may cause failure of structural elements. Identification of incipient fatigue damage is essential to ensure safety of structures. Fatigue crack under repeated loads commonly behaves in a nonlinear dynamic manner, typically manifested by both occurrence of higher harmonic components and interaction of harmonic components. Interrogation of nonlinear dynamic manner provides a promising way to characterize structural fatigue damage. This study aims at developing a new method to interrogate nonlinear dynamic manner for fatigue damage identification. This method is based on bispectral analysis of structural vibrational responses. This method portrays fatigue damage by inspecting the presence of higher harmonic components and quantifying the interaction of these harmonic components. The method can precisely locate and quantify a small-sized fatigue damage in a cantilever beam, presenting great accuracy in fatigue damage identification.