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Based on pseudo strain energy density (PSED) and grey relation coefficient (GRC), an index is proposed to locate the damage of beam-type structures in time-domain. The genetic algorithm (GA) is utilized to identify the structural damage severity of confirmed damaged locations. Furthermore, a systematic damage identification program based on GA is developed on MATLAB platform. ANSYS is employed to conduct the finite element analysis of com- plicated civil engineering structures, which is embedded with interface technique. The two-step damage identification is verified by a finite element model of Xinxingtang Highway Bridge and a laboratory beam model based on polyvi- nylidens fluoride (PVDF). The bridge model was constructed with 57 girder segments, and simulated with 58 meas- urement points. The damaged segments were located accurately by GRC index regardless of damage extents and noise levels. With stiffness reduction factors of detected segments as variables, the GA program evolved for 150 generations in 6 h and identified the damage extent with the maximum errors of 1% and 3% corresponding to the noise to signal ratios of 0 and 5%, respectively. In contrast, the common GA-based method without using GRC index evolved for 600 generations in 24 h, but failed to obtain satisfactory results. In the laboratory test, PVDF patches were used as dynamic strain sensors, and the damage locations were identified due to the fact that GRC indexes of points near damaged ele- ments were smaller than 0.6 while those of others were larger than 0.6. The GA-based damage quantification was also consistent with the value of crack depth in the beam model.  相似文献   
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简要介绍了三维地震勘探中的测量定点工作,提出了实时动态测量GPSRTK技术,并针对两个工区复杂的地表条件就三维地震测线定点的方法进行了探讨。  相似文献   
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INTRODUCTION Structural damage detection technique addresses the problem of how to locate and detect damage that occurred in a structure by using the observed changes of its dynamic and static characteristics. In recent years, damage assessment of structure has drawn wide attention from various engineering fields. Gen-erally, the existing approaches proposed in this area can be clarified into two major categories: the dy-namic identification methods using dynamic test data and the static …  相似文献   
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