استفاده از الگوریتم رقابت استعماری برای تشخیص آسیب سازه ای
Abstract
1- Introduction
2- Background
3- Proposed algorithm
4- Case studies
5- Conclusions
References
Abstract
In practical damage detection problems, experimental modal data is only available for a limited number of modes and in each mode, only a limited number of nodal points are recorded. In using modal data, the majority of the available damage detection solution techniques either require data for all the modes, or all the nodal data for a number of modes; neither of which may be practically available through experiments. In the present study, damage identification is carried out using only a limited number of nodal data of a limited number of modes. The proposed method uses the imperialist competitive optimization algorithm and damage functions. To decrease the number of design variables, several bilinear damage functions are defined to model the damage distribution. Damage functions with both variable widths and variable weights are proposed for increased accurately. Four different types of objective functions which use modal responses of damaged structure are investigated with the aim of finding the most suitable function. The efficiency of the proposed method is investigated using three benchmark numerical examples using both clean and noisy modal data. It is shown that by only using a limited number of modal data, the proposed method is capable of accurately detecting damage locations and reasonably accurately evaluate their extents. The proposed algorithm is most effective with noisy modal data, compared to other available solutions.
Introduction
Damage detection is one of the most active fields of research which has attracted a great deal of interest in recent years [1, 2]. Damage detection techniques have been successfully applied to many practical problems to identify damage through non-destructive tests (NDT). Damage causes a change in the physical properties of the structure, mainly its stiffness, resulting in 3 changes in the dynamic properties of the system such as its natural frequencies, mode shapes, damping ratios and modal strain energies. Therefore, the location of damage and its extent could be identified by monitoring one or more of these properties of the damaged structure. Optimization techniques have long been employed to solve different problems [3, 4], including damage detection problems [5]. Some recent examples may be found in references [6- 8]. Genetic algorithm (GA) is a global optimization technique which has recently been improved and hybridized with other meta-heuristic methods to solve damage detection problems [9-11]. Particle swarm optimization (PSO) is also a useful optimization technique which is frequently applied in the area of topology and shape optimization of structures [12, 13]. PSO has also been used to solve damage detection problems [14, 15]. For a comprehensive review of hybridization of metaheuristic and mathematical programming methods, we refer the interested reader to the survey in [4] and the works [3] and [16]. A hybridization of PSO and linear programming was adopted recently to solve damage detection problems [17]. Another, powerful meta-heuristic algorithm is the imperialist competitive algorithm (ICA), proposed by Atashpaz-Gargari and Lucas to solve optimization problems [18]. This algorithm is a socio-politically motivated optimization algorithm and has shown great performance in both convergence rate and better identification of global optima. Its applicability, effectiveness and limitations were investigated in [19]. Researchers have applied the ICA to solve different optimization problems [19-22].