玻璃纤维增强复合材料（Glass Fiber Reinforced Polymer, GFRP）在长期服役过程中易产生损伤,其中针对平底孔缺陷难以实现高对比度成像与精确定位的问题,本文开展了基于微波反射法的缺陷检测与成像研究。首先分析了GFRP中电磁波传播特性及内部介电不连续界面对反射系数的影响。构建了基于反射特征增强的缺陷定位与成像方法,结合反射异常谱分析、递增间隔约束峰值识别以及二维空间精细定位,实现了对背面非均匀间隔分布的8 mm平底孔缺陷进行稳定识别与精确定位。结果表明,该方法能够有效抑制背景干扰,显著提高缺陷与基体之间的成像对比度,成像结果与缺陷实际分布具有良好一致性。研究结果表明,所提出的方法适用于GFRP内部典型缺陷的无损检测与可视化表征,为复合材料结构损伤的高质量无损成像检测提供技术参考。
Abstract
Glass Fiber Reinforced Polymer (GFRP) is prone to damage during long-term service. Among its defects, flat-bottom hole defects are particularly challenging for achieving high-contrast imaging and precise localization. This study focuses on defect detection and imaging using a microwave reflection method. Firstly, the electromagnetic wave propagation characteristics in GFRP and the impact of internal dielectric discontinuities on reflection coefficients were analyzed. A defect localization and imaging method based on enhanced reflection features was developed. By combining reflection anomaly spectrum analysis, incrementally constrained peak identification, and fine two-dimensional spatial localization, stable detection and precise positioning of 8 mm flat-bottom hole defects with non-uniform distribution on the back side was achieved. The results indicate that this method can effectively suppress background interference, significantly improve the imaging contrast between defects and the matrix, and produce imaging results that closely match the actual defect distribution. The findings demonstrate that the proposed method is suitable for nondestructive testing and visual characterization of typical internal defects in GFRP, providing a technical reference for high-quality nondestructive imaging detection of composite material structural damage.
关键词
微波无损检测 /
玻璃纤维增强复合材料 /
缺陷 /
定位 /
成像
Key words
Microwave nondestructive testing /
Glass fiber reinforced composite material /
Defect /
Localization /
Imaging
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参考文献
[1] BACHMANN J, HIDALGO C, BRICOUT S.Environmental analysis of innovative sustainable composites with potential use in aviation sector—A life cycle assessment review[J]. Science China Technological Sciences, 2017,60(9):1 301-1 317.
[2] 黄领才. 纤维增强聚合物复合材料无损检测方法进展[J].航空学报, 2024,45(5):98-124.
[3] DING F, CAI Y Q, TU W L, et al.Research on ultrasonic non-destructive detection method for defects in GFRP laminates based on machine learning[J]. Ocean Engineering, 2025, 327: 120 972.
[4] SENCK S, SCHEERER M, REVOL V, et al.Microcrack characterization in loaded CFRP laminates using quantitative two-and three-dimensional X-ray dark-field imaging[J]. Composites Part A: Applied Science and Manufacturing, 2018,115:206-214.
[5] DERUSOVA D A, VAVILOV V P, SHPILNOI V, et al.Characterising hidden defects in GFRP/CFRP composites by using laser vibrometry and active IR thermography[J]. Nondestructive Testing and Evaluation, 2022,37(6):776-794.
[6] LI Z, MENG Z Z, FEI F, et al.Enhanced microwave waveguide probe-based methods for damage detection of GFRP composites[J]. NDT & E International, 2025,158:103 572.
[7] 刘增华,吴育衡,王可心,等.基于太赫兹时域光谱技术的陶瓷基复合材料缺陷检测成像研究[J]. 机械工程学报, 2023,59(14):33-42.
[8] YANG X H, FANG Y, WANG R N, et al.Visual quantitative detection of delamination defects in GFRP via microwave[J]. Sensors, 2023, 23(14):6 386.
[9] 胡金花,李勇,谭建国,等.玻璃纤维增强复合材料局部减薄损伤的微波无损定量检测[J].传感器与微系统, 2020,39(3):113-116.
[10] 回沛林,李勇,王若男,等.GFRP材料损失缺陷的微波反射定量检测[J].传感器与微系统,2021,40(7):110-113.
[11] SHRIFAN N H M M, JAWAD G N, ISA N A M, et al. Microwave nondestructive testing for defect detection in composites based on K-means clustering algorithm[J]. IEEE Access, 2020,9:4 820-4 828.
[12] SUTTHAWEEKUL R, TIAN G Y, WANG Z J, et al.Microwave open-ended waveguide for detection and characterisation of FBHs in coated GFRP pipes[J]. Composite Structures,2019, 225: 111 080.
基金
太行国家实验室科研项目（技术基础类）(S2024-5-006); 中国特检院内部项目2023青年10（2023youth10）
