چكيده به لاتين
Abstract:
The structural damage detection has particular importance both economically and from user safety point of view in order to prevent the damage to be widened all over the structure. Thus, various approaches had been presented to achieve this aim. The structural health monitoring methods have been classified into three main categories including destructive, semi-destructive and non-destructive methods. Among the abovementioned methods, vibration based global methods are preferred since they make no harm to structures and are feasible to tackle with different damage scenarios. These methods are divided into four main groups according to the dynamic parameters studied– each of them has their own advantages and limitations. All global damage detection methods are based on comparing measured responses of the real world structure with those of the analytical model. The structural health monitoring methods mainly focus on determining exact location and severity of the damage based on incomplete data extracted from the real world structure due to the fact that the complete real modal information might not be available. In this study, a damage detection method based on both frequency and mode shapes is proposed which utilizes the incomplete modal data. The failure assessment problem can be formulated as an optimization problem. To this end, the damage in a member is simulated as a reduction in its corresponding stiffness employing appropriate reduction factors. These factors are considered as the main variables of the optimization problem– we subsequently determine them by solving the problem through a Genetic Algorithm (GA). Several examples, including eleven simple and complex structural models, have been studied considering various damage intensities, various damage scenarios and the effect of the noise in modal data. The results obtained have been compared and contrasted with those of available results in the previous studies. The comparisons show the efficiency and viability of the proposed approach in detecting the correct location of the damage and its severity. The results also suggest that the method could successfully deal with incomplete and noisy modal data.
Keywords: Damage detection, Model updating, Metaheuristic optimization, incomplete methods
