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中文核心期刊

基于红外雷达热波的碳纤维复合材料缺陷深度估测方法

DEFECT DEPTH PREDICTION OF CFRP COMPOSITES USING THERMAL WAVE RADAR

  • 摘要: 碳纤维复合材料(Carbon fiber reinforced polymer, CFRP)转向架具有密度小、比强度高等优点, 对于动车组轻量化具有重大意义. 但是CFRP各向异性的特点使其内部易产生气孔、分层等缺陷, 严重影响结构的使用性能. 红外雷达热波是一种主动热成像无损检测技术, 可对复合材料中的缺陷进行定性与定量分析, 该技术通过施加宽带频率调制热激励并结合信号处理算法来检测内部缺陷. 然而现有研究主要是针对缺陷对比度增强的定性检测, 对缺陷深度的定量分析较少. 本文基于红外雷达热波技术提出了一种估测材料内部缺陷深度的新方法. 首先提出以相位差峰值作为缺陷深度估测的新特征量, 理论分析与数值模拟均表明相位差峰值与缺陷深度呈线性关系; 其次揭示了缺陷尺寸对相位差峰值与缺陷深度线性关系的影响, 引入缺陷直径作为修正因子构建复合变量, 解决了不同尺寸同深度缺陷深度估测误差大的问题; 最后建立了适用于红外雷达热波技术的缺陷深度定量估测流程, 实现单次热加载下不同尺寸、深度缺陷的高精度深度估测, 提升了检测效率与工程适用性. 本文对碳纤维复合材料层压板试样内的6个不同尺寸与深度的缺陷进行检测, 平均测量误差仅为8 %, 并讨论了不同材料热属性以及红外雷达热波参数的影响. 本研究将丰富CFRP 转向架缺陷的定量无损检测手段, 为动车组转向架的轻量化提供安全可靠的保障.

     

    Abstract: Carbon fiber reinforced polymer (CFRP) bogies offer advantages such as low density and high specific strength, making them highly significant for reducing the weight of electric multiple units. However, the anisotropic nature of CFRP makes it prone to internal defects like voids and delamination, which severely compromise the structural performance. Thermal wave radar is a non-destructive testing technique based on active thermography capable of performing both qualitative and quantitative analyses of defects in composites. This technology detects internal defects by employing broadband frequency-modulated thermal excitation combined with advanced signal processing algorithms. However, existing research has primarily focused on qualitative defect detection such as defect contrast enhancement, with limited quantitative analysis of defect depth. This study proposes a novel method for estimating internal defect depth based on thermal wave radar technology. Firstly, phase contrast peak value is proposed as a new feature for estimating defect depth. Both theoretical analysis and numerical simulation indicate that the peak phase contrast exhibits a linear relationship with defect depth. Secondly, it reveals the influence of defect size on the linear relationship between phase contrast peak values and defect depth. The defect diameter is induced as a correction factor to construct a composite variable. This addresses significant estimation errors for defects of different sizes at the same depth. Thirdly, a quantitative workflow is established for estimating the depth of defects using infrared thermal wave radar technology. This enables the precise estimation of the depth of defects of different sizes and depths under a single thermal loading. This enhances both detection efficiency and engineering applicability. Six defects with varying sizes and depths in carbon fiber reinforced polymer laminate yielded an average measurement error of only 8%. The influence of material thermal properties and thermal wave radar parameters are also discussed. This study will enhance quantitative non-destructive testing methods for CFRP bogie defects, providing a safe and reliable foundation for lightweighting high-speed train bogies.

     

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