赵林鑫, 江守燕, 杜成斌. 基于SBFEM和机器学习的薄板结构缺陷反演[J]. 工程力学, 2021, 38(6): 36-46. DOI: 10.6052/j.issn.1000-4750.2020.06.0416
引用本文: 赵林鑫, 江守燕, 杜成斌. 基于SBFEM和机器学习的薄板结构缺陷反演[J]. 工程力学, 2021, 38(6): 36-46. DOI: 10.6052/j.issn.1000-4750.2020.06.0416
ZHAO Lin-xin, JIANG Shou-yan, DU Cheng-bin. FLAWS DETECTION IN THIN PLATE STRUCTURES BASED ON SBFEM AND MACHINE LEARNING[J]. Engineering Mechanics, 2021, 38(6): 36-46. DOI: 10.6052/j.issn.1000-4750.2020.06.0416
Citation: ZHAO Lin-xin, JIANG Shou-yan, DU Cheng-bin. FLAWS DETECTION IN THIN PLATE STRUCTURES BASED ON SBFEM AND MACHINE LEARNING[J]. Engineering Mechanics, 2021, 38(6): 36-46. DOI: 10.6052/j.issn.1000-4750.2020.06.0416

基于SBFEM和机器学习的薄板结构缺陷反演

FLAWS DETECTION IN THIN PLATE STRUCTURES BASED ON SBFEM AND MACHINE LEARNING

  • 摘要: 将比例边界有限元法(Scaled Boundary Finite Element Method,SBFEM)和机器学习算法相结合,基于Lamb波在含缺陷薄板结构中传播时结构的动力响应变化定量反演结构中的缺陷信息。SBFEM通过改变裂纹所在子域的比例中心位置反映不同的裂纹信息,减少了需要进行重划分的网格数量,大大提升了计算效率,能够提供足够多的反映缺陷特性的训练数据;基于极限学习机的人工神经网络机器学习模型避免了传统反分析问题求解的目标函数极小化迭代过程,能在极快的学习速度下保证缺陷反演的精度。因此,提出的缺陷反演模型大大减少了运算时间成本。若干数值算例表明:建立的反演分析模型能够根据含缺陷的薄板结构Lamb波传播时观测点的动响应信号,准确地探测出薄板结构中的开口裂纹状缺陷的位置和大小等信息,并具有很高的反演效率,且在信号含有噪声的情况下仍具有较好的鲁棒性。

     

    Abstract: Combining Scaled Boundary Finite Element Method (SBFEM) and machine learning algorithm, the flaw information in the structure is quantitatively reversed based on the dynamic responses of the structure when the Lamb wave propagates in the thin plate structure with flaws. By changing the scaled center position of the subdomain where the crack is located to reflect different crack information, the SBFEM minimize the remeshing processes and improve the computational efficiency. It can provide enough training data reflecting flaw characteristics. The extreme learning machine, a machine learning model based on artificial neural network, avoids the iterative process of minimizing the objective function in the traditional inversion analysis, and can guarantee the precision of flaw detection with extremely fast learning speed. Therefore, the proposed inversion model greatly reduces the time-cost for flaw detection. The several numerical examples show that for a thin plate structure with crack-like flaws, the proposed model can accurately detect the location and size of the crack on the grounds of dynamic response signal of the observation point during the propagation of Lamb wave. The method also has high inversion efficiency and it is robust against noise.

     

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