Li Tengteng, Cao Maosen, Li Jianle, Yang Lei, Xu Hao, Wu Zhanjun
State Key Laboratory of Structural Analysis for Industrial Equipment, School of Aeronautics and Astronautics, Faculty of Vehicle Engineering and Mechanics, Dalian University of Technology, Dalian 116024, China.
Department of Engineering Mechanics, Hohai University, Nanjing 210098, China.
Sensors (Basel). 2021 Jan 16;21(2):606. doi: 10.3390/s21020606.
The attempt to integrate the applications of conventional structural deformation reconstruction strategies and vibration-based damage identification methods is made in this study, where, more specifically, the inverse finite element method (iFEM) and pseudo-excitation approach (PE) are combined for the first time, to give rise to a novel structural health monitoring (SHM) framework showing various advantages, particularly in aspects of enhanced adaptability and robustness. As the key component of the method, the inverse finite element method (iFEM) enables precise reconstruction of vibration displacements based on measured dynamic strains, which, as compared to displacement measurement, is much more adaptable to existing on-board SHM systems in engineering practice. The PE, on the other hand, is applied subsequently, relying on the reconstructed displacements for the identification of structural damage. Delamination zones in a carbon fibre reinforced plastic (CFRP) laminate are identified using the developed method. As demonstrated by the damage detection results, the iFEM-PE method possesses apparently improved accuracy and significantly enhanced noise immunity compared to the original PE approach depending on displacement measurement. Extensive parametric study is conducted to discuss the influence of a variety of factors on the effectiveness and accuracy of damage identification, including the influence of damage size and position, measurement density, sensor layout, vibration frequency and noise level. It is found that different factors are highly correlated and thus should be considered comprehensively to achieve optimal detection results. The application of the iFEM-PE method is extended to better adapt to the structural operational state, where multiple groups of vibration responses within a wide frequency band are used. Hybrid data fusion is applied to process the damage index (DI) constructed based on the multiple responses, leading to detection results capable of indicating delamination positions precisely.
本研究尝试将传统结构变形重建策略的应用与基于振动的损伤识别方法相结合，更具体地说，首次将逆有限元法（iFEM）和虚拟激励法（PE）相结合，从而产生了一种具有多种优势的新型结构健康监测（SHM）框架，特别是在增强适应性和鲁棒性方面。作为该方法的关键组成部分，逆有限元法（iFEM）能够基于测量的动态应变精确重建振动位移，与位移测量相比，这在工程实践中更能适应现有的车载SHM系统。另一方面，随后应用虚拟激励法（PE），依靠重建的位移来识别结构损伤。使用所开发的方法识别碳纤维增强塑料（CFRP）层压板中的分层区域。如损伤检测结果所示，与依赖位移测量的原始PE方法相比，iFEM-PE方法具有明显提高的精度和显著增强的抗噪声能力。进行了广泛的参数研究，以讨论各种因素对损伤识别有效性和准确性的影响，包括损伤大小和位置、测量密度、传感器布局、振动频率和噪声水平的影响。发现不同因素高度相关，因此应综合考虑以获得最佳检测结果。iFEM-PE方法的应用得到扩展，以更好地适应结构运行状态，其中使用宽频带内的多组振动响应。应用混合数据融合来处理基于多个响应构建的损伤指标（DI），从而得到能够精确指示分层位置的检测结果。
