Local damage detection of membranes based on Bayesian operational modal analysis and three-dimensional digital image correlation
Local damage detection of membranes based on Bayesian operational modal analysis and three-dimensional digital image correlation
复制标题
DOI：
10.1016/j.ymssp.2019.04.051
复制
发表时间：
2019-09-15
影响因子：
8.4
通讯作者：
Xu, Yongfeng
中科院分区：
文献类型：
--
作者：
Hu, Yujia;Guo, Weigong;Xu, Yongfeng
基于模态分析的结构局部损伤检测是一个难点。提出了一种结合贝叶斯操作模态分析（BOMA）和三维数字图像相关（3D-DIC）的环境激励下薄膜局部损伤检测新方法。它是一种非接触的、全场动态的方法，不需要在测试膜上附着传感器。BOMA和3D-DIC方法的优点集成在这项工作中。可以清楚地观察到由局部损伤引起的模态和曲率模态的异常。此外，振型损伤指数（MSDI）被用来改善局部损伤检测，和结构损伤可以识别的邻域与高值的MSDI。作为示范，该方法被应用于检测具有不同边界条件的圆形和矩形膜中剃刀切割引入的损伤。(C)2019由Elsevier Ltd.出版
It is difficult to detect local damage of a structure based on modal analysis. This paper presents a novel local damage detection method of membranes under ambient excitation, which combines Bayesian operational modal analysis (BOMA) and three-dimensional digital image correlation (3D-DIC). It is a noncontact and full-field dynamic method with no sensors attached on a test membrane. Advantages of BOMA and 3D-DIC methods are integrated in this work. Anomalies caused by local damage in mode shapes and curvature mode shapes can be explicitly observed. Moreover, a mode shape damage index (MSDI) is used to improve local damage detection, and structural damage can be identified in neighborhoods with high values of MSDIs. The methodology is applied, as a demonstration, to detect damage introduced by razor cuts in circular and rectangular membranes with different boundary conditions. (C) 2019 Published by Elsevier Ltd.