A two-stage method to identify structural damage sites and extents by using evidence theory and micro-search genetic algorithm
A two-stage method to identify structural damage sites and extents by using evidence theory and micro-search genetic algorithm
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DOI：
10.1016/j.ymssp.2008.07.008
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发表时间：
2009-04
影响因子：
8.4
通讯作者：
H. Guo;Zhengliang Li
中科院分区：
文献类型：
--
作者：
H. Guo;Zhengliang Li
本文提出了一种利用信息融合技术和遗传算法确定结构多处损伤位置和程度的两阶段方法。首先，损伤识别策略是利用证据理论对损伤位置进行定位，将来自固有频率和振型的损伤识别信息完美地结合在一起。然后，提出了一种微搜索遗传算法(MSGA)来确定结构的损伤程度。以悬臂梁为例，比较了该方法与多损伤位置确定准则(MDLAC)和简单遗传算法的性能。仿真结果表明，证据理论的识别结果优于频率MDLAC方法和振型MDLAC方法，MSGA也比简单遗传算法更准确有效。因此，两阶段法对于结构的多重损伤识别是非常有效的。
A two-stage method of determining the location and extent of multiple structural damages by using information fusion technique and genetic algorithm is presented in this paper. First the damage detection strategy is to localize the damage sites by using an evidence theory, which can perfectly integrate the damage identification information coming from both natural frequencies and mode shapes. Then, a micro-search genetic algorithm (MSGA) is proposed to determine the damage extent. A cantilever beam is analyzed as a numerical example to compare the performance of the proposed method with the multiple damage location assurance criterions (MDLAC) and the simple genetic algorithms. Simulation results show that identification results of the evidence theory are better than those both of the frequency MDLAC method and the mode shape MDLAC method, and the MSGA is also more accurate and effective than the simple genetic algorithms. Therefore, the two-stage method is very effective for the identification of multiple structural damages.