چكيده به لاتين
Transport systems, especially bridges in many cities and suburban arteries due to long time service are prone to structural failure. Environmental impact, changes in the characteristics loads, earthquakes, and tructural defect caused damage on the bridge and complete failure of the bridge. In recent decades, structural health monitoring techniques are deal to with these challenges used in bridges. Health monitoring techniques based on dynamic characteristics and modal features as one of the most widely used techniques is in the process of repair and maintenance structures. In this study, based on vibration characteristics, damage detection of a real bridge with steel girders will be discussed.
In this study, the goal is a process of damage detection bridges based on meta-heuristic optimization algorithms and dynamic characteristics of the bridge. Damage detection problem based on the vibrating characteristics is defined as an optimization problem. Objective function will be defined as natural frequencies basement and a combination of frequency and modal strain energy. After the bridge modeling in ANSYS software, damage scenarios will be applied on finite element model in ANSYS and modal parameters will be extracted. Acquired parameters in this stage are inserted in particle swarm optimization algorithm. The algorithm is conducted with Modal analysis based on finite element codes in MATLAB. According to solving objective functions based on the natural frequency and a combination of modal strain energy and natural frequency, location and severity of damage is identified by algorithm. Based on the responses of the algorithm about the performance of presented method well be discussed. According to gained results, particle swarm optimization algorithm based on the objective function of natural frequency, severity and location of damage properly is detected. In case of objective function based on combination of natural frequency and modal strain energy the algorithm is better performance than prior case.
Keywords: Modal Parameters, Particle Swarm Optimization Algorithm, Finite Element Model, Optimization, Damage Detection.
