On the feasibility of simultaneous identification of a material property of a Timoshenko beam and a moving vibration source

• Published in: Engineering structures Vol. 227; p. 111346
• Main Authors: Guidio, Bruno, Jeong, Chanseok
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 15.01.2021; Elsevier BV
• Subjects: Computer applications; Continuous beams; Continuous bridges; Feasibility studies; Finite element method; Finite element method (FEM); Genetic algorithm (GA); Genetic algorithms; Joint inversion; Material properties; Mechanical properties; Modulus of elasticity; Noise measurement; Parameter identification; Passive wave source-based structural health monitoring (SHM); Spatial variations; Structural health monitoring; Timoshenko beam; Timoshenko beams; Vehicle-induced ambient vibrations; Vibration; Vibration measurement; Vibrations; Wave equations; Finite element method (FEM); Genetic algorithm (GA); Passive wave source-based structural health monitoring (SHM); Joint inversion; Timoshenko beam; Vehicle-induced ambient vibrations
• ISSN: 0141-0296; 1873-7323
• DOI: 10.1016/j.engstruct.2020.111346

•Identifying the material profile of a bridge structure using an unknown moving wave source (e.g., a vehicle) and measured vibration data.•Genetic algorithm-based joint inversion.•Finite element modeling of the wave responses of a Timoshenko-beam continuous bridge model. This paper presents a computational study for investigating the feasibility of simultaneous identification of a material property of a Timoshenko continuous beam and a moving vibration source on the beam by using the data of measured vibrations on it. This work employs the finite element method to solve the wave equations of a Timoshenko beam subject to a moving vibrational source. It uses the Genetic Algorithm (GA) as an inversion solver to identify the values of targeted control parameters that characterize a material property of the beam and a moving vibration source on it. The numerical results show that, first, the presented inversion method can detect the characteristics of a moving wave source as well as the spatial variation of the elastic modulus of a Timoshenko-beam continuous bridge model, which is set to be piece wisely homogeneous in this work. Second, the GA-based joint inversion is effective even when the moving vibrational source’s moving velocity is not constant over time. Third, the detrimental effect of noise in measurement data on the accuracy of the inversion becomes more significant as the number of control parameters increases. By using the presented method, engineers can take advantage of vehicle-induced ambient vibrations on bridges measured by modern sensors for the sake of passive wave source-based structural health monitoring (SHM).