王佳萍, 杜成斌, 王翔, 江守燕. 基于XFEM和改进人工蜂群算法的结构内部缺陷反演[J]. 工程力学, 2019, 36(9): 25-31. DOI: 10.6052/j.issn.1000-4750.2017.11.0874
引用本文: 王佳萍, 杜成斌, 王翔, 江守燕. 基于XFEM和改进人工蜂群算法的结构内部缺陷反演[J]. 工程力学, 2019, 36(9): 25-31. DOI: 10.6052/j.issn.1000-4750.2017.11.0874
WANG Jia-ping, DU Cheng-bin, WANG Xiang, JIANG Shou-yan. INVERSE ANALYSIS OF INTERNAL DEFECTS IN STRUCTURES USING EXTENDED FINITE ELEMENT METHOD AND IMPROVED ARTIFICIAL BEE COLONY ALGORITHM[J]. Engineering Mechanics, 2019, 36(9): 25-31. DOI: 10.6052/j.issn.1000-4750.2017.11.0874
Citation: WANG Jia-ping, DU Cheng-bin, WANG Xiang, JIANG Shou-yan. INVERSE ANALYSIS OF INTERNAL DEFECTS IN STRUCTURES USING EXTENDED FINITE ELEMENT METHOD AND IMPROVED ARTIFICIAL BEE COLONY ALGORITHM[J]. Engineering Mechanics, 2019, 36(9): 25-31. DOI: 10.6052/j.issn.1000-4750.2017.11.0874

基于XFEM和改进人工蜂群算法的结构内部缺陷反演

INVERSE ANALYSIS OF INTERNAL DEFECTS IN STRUCTURES USING EXTENDED FINITE ELEMENT METHOD AND IMPROVED ARTIFICIAL BEE COLONY ALGORITHM

  • 摘要: 将扩展有限元法与智能优化算法相结合,基于结构的实际响应值反演出结构内部缺陷信息。传统人工蜂群算法在一定程度上朝着任意的方向搜索,为了避免出现搜索的局部最优现象,该文在传统人工蜂群算法中嵌入了加权平均数突变和交叉算子,将这种改进算法用于单个圆形、椭圆形缺陷和两个不规则缺陷的反演分析,并研究了该算法在测得值有误差情况下的适应性。研究得到:这种改进人工蜂群算法能准确反演出结构的真实缺陷信息;改进人工蜂群算法相比于传统人工蜂群算法收敛速度更快且不易出现局部最优,且定位准确,鲁棒性较强。

     

    Abstract: The information of defect in a structure is determined using the extended finite element method combined with a kind of improved artificial bee colony algorithm, based on real structural response. As searching optimal value may appear in an arbitrary direction in traditional artificial bee colony (ABC) algorithm, weighted average mutation and a cross operator are introduced to avoid the local optimum in the optimizing. The presented inverse method is also used to determine the location of a single-circular-like defect and an elliptical-like defeat and two irregular defects, and the robustness of the algorithm under the condition of measuring error is also studied. The numerical results indicate that the adapting artificial bee colony (AABC) algorithm proposed can present the real information of defects accurately. The convergence speed of AABC is faster than that of traditional ABC, and it is unlikely that the local optimum will appear in the optimizing. The presented method can locate the defects accurately and show a high robustness.

     

/

返回文章
返回