An Yonghui, Pang Chaozhi, Cui Ranting, Ou Jinping
State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures (Provincially and Ministerially Co-constructed), Guangxi University, Nanning 530004, China; Department of Civil Engineering, Dalian University of Technology, Dalian 116023, China.
State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures (Provincially and Ministerially Co-constructed), Guangxi University, Nanning 530004, China.
Ultrasonics. 2025 May;149:107592. doi: 10.1016/j.ultras.2025.107592. Epub 2025 Feb 2.
The application of Carbon Fiber Reinforced Polymer (CFRP) in reinforcing steel structures is widely recognized. However, there is relatively little research on the localization and imaging of debonding damage in CFRP-reinforced steel structures. This paper proposes a probabilistic imaging method improved by ultrasonic guided-wave transfer function to localize debonding damage in CFRP-reinforced steel structures. Firstly, this study proposes a waveform feature index that exhibits strong robustness against debonding damages while exhibiting minimal susceptibility to environmental disturbances, which enhances the detection capability for small-scale debonding damages compared to traditional linear indices. Secondly, the proposed method replaces the conventional fixed array with a dynamic scanning approach. This method achieves 2D debonding damage imaging by leveraging information solely from orthogonal directions, which not only drastically reduces the number of sensors but also enables flexible adjustment of the detection area, thereby enhancing its applicability. Thirdly, the proposed waveform feature index is independent of the amplitude of the excitation/receiving signal. Therefore, the proposed method maintains accurate localization of debonding damage during damage imaging detection, regardless of variations in coupling conditions between the sensor and the structure under inspection. The efficacy of the proposed method is validated through comprehensive numerical simulations and experiments. The results demonstrate its ability to accurately detect and localize damage in CFRP-reinforced steel plate structures, offering an effective and precise way for early debonding detection.
碳纤维增强聚合物（CFRP）在钢结构加固中的应用已得到广泛认可。然而，关于CFRP加固钢结构中脱粘损伤的定位与成像的研究相对较少。本文提出一种基于超声导波传递函数改进的概率成像方法，用于定位CFRP加固钢结构中的脱粘损伤。首先，本研究提出一种波形特征指标，该指标对脱粘损伤具有很强的鲁棒性，同时对环境干扰的敏感性最小，与传统线性指标相比，增强了对小规模脱粘损伤的检测能力。其次，所提出的方法用动态扫描方法取代了传统的固定阵列。该方法仅利用来自正交方向的信息实现二维脱粘损伤成像，这不仅大幅减少了传感器数量，还能灵活调整检测区域，从而提高了其适用性。第三，所提出的波形特征指标与激励/接收信号的幅度无关。因此，所提出的方法在损伤成像检测过程中，无论传感器与被检测结构之间的耦合条件如何变化，都能保持对脱粘损伤的准确定位。通过全面的数值模拟和实验验证了所提方法的有效性。结果表明其能够准确检测和定位CFRP加固钢板结构中的损伤，为早期脱粘检测提供了一种有效且精确的方法。
