基于最小二乘逆时偏移(LSRTM)的复合材料层合板导波损伤成像

Jiaze He, A. Schwarberg
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摘要

提出了一种将最小二乘逆时偏移(LSRTM)应用于复合材料层合板超声导波成像的方法。随着复合材料在航空航天等领域的应用越来越广泛,对结构健康监测(SHM)和无损检测(NDE)中高分辨率成像的需求也越来越大。例如,分层是复合材料层合板的常见问题,这在一定程度上导致了复合材料用于承重结构的忧虑。尽管使用传统逆时偏移(RTM)方法的基于求解器的成像技术可以通过广泛的损伤散射效应来显示损伤,但由于数据采集孔径、传感器密度、频率/波长以及伴随重建的不完全性,所得到的图像不能完全定义损伤区域。在此之前,我们已经推导了LSRTM理论,并对其在各向同性板上的高分辨率损伤成像性能进行了基准测试。为了提高复合材料层合板的损伤成像能力,本文提出了一种基于各向异性材料的超声导波LSRTM方法。给出了正演算子和伴随算子的推导。数值算例研究表明,LSRTM比RTM在复合材料板损伤映射方面有更大的改进。在基于Born近似模型的数值研究中,产生了多个损伤部位或具有复杂形状的损伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Guided Wave Damage Imaging of Composite Laminates With Least-Squares Reverse-Time Migration (LSRTM)
A method for adapting least-squares reverse time migration (LSRTM) for ultrasonic guided wave imaging of composite laminates is proposed in this paper. As composites become more widely used in fields such as the aerospace industry, the need for high resolution imaging in structural health monitoring (SHM) and nondestructive evaluation (NDE) is also growing. For instance, delamination is a common problem in composite laminates, which has led to a certain degree of apprehension in the use of composite materials for load-bearing structures. Although the solver-based imaging techniques using conventional reverse time migration (RTM) methods illuminate damage with a wide range of damage-scattering effects, the resulted images do not fully define the damage regions due to the limited data acquisition aperture, sensor density, frequencies/wavelengths, and incompleteness of adjoint reconstruction. Previously, we have derived the LSRTM theory and benchmarked its high-resolution damage imaging performance for isotropic plates. To improve damage imaging in composite laminates, this paper proposes to create an ultrasonic guided wave-based LSRTM method for anisotropic materials. The derivation of the forward modeling operator and the adjoint operator is presented. Numerical case studies were conducted to show the improvement of LSRTM over RTM in mapping damage in composite plates. Multiple damage sites or damage with a complex shape were created in the numerical studies based on Born approximation-based modeling.
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