Identification Of Structural System Based On Particle Swarm Optimization

Vibration-based structural system identification methods have attracted considerable attention in recent years for the assessment of health and safety of civil structures. Most currently used vibration-based structural system identification methods are applicable only under the assumption that some parameters of systems are known in advance. However, in the real world, parameters may be difficult to determine due to the complexity of structural systems. Therefore, there is significant interest in developing a feasible method for obtaining the physical characteristics of the system that uses as little information as possible.System identification is an inverse problem of using measured data from a system to estimate quantities that give a complete description of the system according to some representative model of it. Difficulties lie in the development of algorithms that use measured data from the system to characterize it without significant a priori knowledge of the system. A method for identification of structural systems using Particle Swarm Optimization(PSO) algorithm is presented to overcome some of the difficulties encountered in the field. The PSO algorithm is a new evolutionary computation method which is applicable to complex optimization problems that are nonlinear, nondifferentiable and multimodal. The basic idea of the method is that the identification problems are cast as a multimodal nonlinear programming problem, and then PSO algorithm is used to find the optimal estimation of the parameters. Some results obtained with this algorithm are presented for the identification of structural systems under conditions including limited input/output data, noise polluted signals, and no prior knowledge of mass, damping, or stiffness of the system. The numerical examples show that the PSO method is easy to implement, computationally inexpensive, and is successful for structural system identification.The main contents are listed as follow:1. The research state of Structure Health Monitoring(SHM) system and structural system identification(SI) are briefly reviewed. Then the traditional methods and the new methods of SI are introduced. At last, the main research contents in this thesis are outlined.2. The research state and application of the PSO algorithm are briefly reviewed.3. The impact of key parameters such as inertia weight, acceleration coeficient and swarm size on the performance of PSO is studied. Based on this analysis, a satisfied parameter set is obtained.4. A PSO-based system identification method in civil engineering is developed. Simulation results based on the identification of 6-degree and 10-degree of freedom structural systems demonstrate the effectiveness and feasibility of the proposed method.5. At last, the thesis ends with some conclusions from the research.