热障涂层孔隙结构超声多重散射机制及孔隙率定量表征

The thermal-insulation and oxidation-resistance of thermal barrier coatings (TBCs) is significantly depended on its internal pore microstructure. It is difficult to achieve a quantitative characterization of porosity using conventional ultrasonic technique, due to the elastic anisotropy from the pore microstructure including random pore size and anisotropic pore orientation that causes complicated ultrasonic scattering mechanism. In this project, based on the Maxwell homogenization scheme for anisotropic elastic materials, the pore microstructure of TBCs is described by average pore size a, aspect ratios α, and orientation probability density P(ψ,λ). The acoustic scattering response of TBCs is investigated by considering the dependence of anisotropic elastic tensor and pore multi-feature parameters. The wave number depended on pore size, pore orientation and elastic tensor is derived and used to reveal the acoustic multiple scattering mechanism in TBCs. Then, ultrasonic detecting scheme is constructed utilizing the characteristic response signals related with pore multi-feature parameters, which resolves the problems that two independent elastic tensors can’t clarify the acoustic multiple scattering mechanism of anisotropic elastic TBCs. Consequently, the disturbances of thin thickness, random pore size and anisotropic pore orientation in characteristic response signals are decoupled, and a least-square method with cross-correlation algorithm is proposed to solve the characteristic response signals and achieve ultrasonic quantitative nondestructive characterization of porosity in TBCs. This project is important for ensuring the TBCs high comprehensive performance and improving the service life of TBCs components.

热障涂层内部孔隙结构是隔热、抗氧化性能的决定因素，现有涂层孔隙尺寸随机分布、结构取向各向异性等微观特征引起的弹性各向异性，导致声波散射机制复杂、孔隙率超声定量表征困难的问题。本项目基于微观力学Maxwell均匀方案，选用孔隙平均尺寸a、宽高比α、取向概率密度P(ψ,λ)等描述热障涂层孔隙结构，将涂层孔隙多特征参数与弹性各向异性张量的依赖关系引入介质的超声散射模型，通过与孔隙尺寸、取向以及弹性均相关的复波数描述弹性各向异性介质中的超声多重散射机制，进而构建孔隙多特征参数与超声特征检测信号定量关系的检测模型，突破两个独立弹性张量无法阐明热障涂层弹性各向异性特征下的超声散射机制的局限。建立从特征检测信号中解耦薄厚度、孔隙尺寸与取向等干扰的方法，提出特征检测信号的孔隙率最小二乘法-互相关法解析策略，实现热障涂层孔隙率的准确表征。该研究工作为控制热障涂层综合性能、提高涂层工件服役寿命提供重要的保障。

热障涂层内部孔隙结构是隔热、抗氧化性能的决定因素，现有涂层孔隙尺寸随机分布、结构取向各向异性等微观特征引起的弹性各向异性，导致声波散射机制复杂、孔隙率超声定量表征困难的问题。本项目提出了采用“弹性各向异性介质超声多重散射机制正演+面向材料特征检测信号机器学习反演”的创新策略。基于微观力学Maxwell均匀方案，选用孔隙平均尺寸a、宽高比α、取向概率密度P(ψ,λ)等描述热障涂层孔隙结构，将涂层孔隙多特征参数与弹性各向异性张量的依赖关系引入介质的超声散射模型，通过与孔隙尺寸、取向以及弹性均相关的复波数描述弹性各向异性介质中的超声多重散射机制，进而构建了孔隙多特征参数与超声特征检测信号定量关系的检测模型，突破了两个独立弹性张量无法阐明热障涂层弹性各向异性特征下的超声散射机制的局限。提出了从特征检测信号中解耦薄厚度、孔隙尺寸与取向等干扰的方法，提出了特征检测信号的孔隙率最小二乘法-互相关法解析策略，研发了热障涂层孔隙率超声检测新技术, 率先实现了未知孔隙率涂层的预测相对误差小于6.37%，比单独采用BP神经网络或GPR算法预测孔隙率的准确率分别提高32%和48%。该研究工作为控制热障涂层综合性能、提高涂层工件服役寿命提供重要的保障。

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