In this paper, a methodology for the detection and localization of damages in composite pultruded members is proposed. This is particularly relevant to thin-walled pultruded members, which are typically characterized by orthotropic behavior, anisotropic along the fibers and isotropic in the cross section. Hence, a method to detect and localize damage, and the influence these might have on the performance of thin-walled Glass Fiber Reinforced Polymer (GFRP) members, is proposed and applied to both numerical and experimental data. Specifically, the numerical and experimental modal shapes of a narrow flange pultruded profile are analyzed. The reliability of the proposed semiparametric statistical method, which is based on Gaussian Processes Regression and Bayesian-based Recursive Partitioning, is analyzed on a narrow flange profile, artificially affected by sawed notches with incremental depth. The numerical investigation is carried out via finite element models (FEMs) of the cracked beam, where the dynamic parameters and the modal shapes are computed. In total, three different crack sizes are investigated, to compare the results with the experimental ones. Finally, the proposed approach is further extended and validated on numerically simulated frame structures.

中文翻译：

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用于检测和定位拉挤玻璃纤维增​​强聚合物材料损伤的递归分配和高斯过程回归

在本文中，提出了一种检测和定位复合材料拉挤构件损伤的方法。这与薄壁拉挤构件特别相关，其典型特征是正交各向异性、沿纤维各向异性和横截面各向同性。因此，提出了一种检测和定位损伤的方法，以及这些方法可能对薄壁玻璃纤维增​​强聚合物 (GFRP) 构件的性能产生的影响，并将其应用于数值和实验数据。具体而言，分析了窄翼缘拉挤型材的数值和实验模态形状。所提出的基于高斯过程回归和基于贝叶斯的递归分区的半参数统计方法的可靠性在窄法兰轮廓上进行了分析，受锯切槽口深度增加的人为影响。数值研究是通过裂纹梁的有限元模型 (FEM) 进行的，其中计算了动态参数和模态形状。总共研究了三种不同的裂纹尺寸，以将结果与实验结果进行比较。最后，在数值模拟的框架结构上进一步扩展和验证了所提出的方法。