风电叶片复合材料微波热成像缺陷定量检测理论和方法研究

In order to solve the problems of low detection efficiency of wind turbine blade, lack of research on the theory of microwave thermography non-destructive testing and lack of defect depth and size quantification method, this project proposes the approaches of microwave thermography for defect detection and quantification. Through theory analysis, numerical simulations and experimental studies, the project will investigate mainly the following contents: microwave heating principle of wind turbine blade composites with different properties, the influence of defect property on the heat transfer field and temperature field, measurement system optimization and specimens design methods, microwave pulsed phase thermography frequency domain processing method, fast extraction algorithm for the phase characteristics in the frequency domain, defect depth quantification and correction method, adaptive sparse matrix of fast imaging with different types of defects and auto defect separation, defect area quantification. Also, this project is planned to break through the following key technologies: multi-layers multi-physics fields’ model construction considering the composite, parameter optimization for microwave heating sensor and signal excitation, fast matrix processing of sequence image et al. Based on these, the theory foundation for microwave thermography detection will be expounded, the approaches for composite inner defect depth quantitative detection will be built, and auto-separation based on adaptive sparse matrix will be established, which will provide a visualized and effective means for quality control of wind turbine blade in manufacturing process and in service.

针对当前风电叶片复合材料检测效率较低、微波热成像无损检测理论研究相对薄弱、缺陷深度及损伤面积的定量方法不足等问题，提出面向风电叶片复合材料的微波热成像缺陷定量检测方法。项目拟采用理论分析、数值仿真、实验研究等手段，研究多种风电叶片复合材料的微波加热原理、缺陷属性变化对热传导场和温度场的影响机理、试验系统优化与试件设计方法、微波脉冲相位热成像的频域处理方法、频域相位谱特征值的快速提取算法、缺陷深度定量与校正方法、自适应稀疏矩阵对不同类型缺陷的快速成像和自动分离、缺陷损伤面积的定量方法等内容，重点突破多层各向异性复合材料的多物理场建模、微波激励传感器及激励信号的参数优化、图像序列的快速矩阵处理等关键技术。在此基础上，阐明微波热成像缺陷检测的理论，建立复合材料内部缺陷的深度定量检测方法和基于自适应稀疏矩阵的缺陷自动分离和面积定量方法，为风电叶片的质量控制和在役检测提供一种直观而高效的手段。

本项目采用理论分析、数值仿真、实验研究等手段，研究多种风电叶片复合材料的微波加热原理、缺陷属性变化对热传导场和温度场的影响机理、试验系统优化与试件设计方法、微波脉冲相位热成像的频域处理方法、频域相位谱特征值的快速提取算法、缺陷深度定量与校正方法、自适应稀疏矩阵对不同类型缺陷的快速成像和自动分离、缺陷损伤面积的定量方法等内容，重点突破了多层各向异性复合材料的多物理场建模、微波激励传感器及激励信号的参数优化、图像序列的快速矩阵处理等关键技术。针对当前风电叶片复合材料检测效率较低、微波热成像无损检测理论研究相对薄弱、缺陷深度及损伤面积的定量方法不足等问题，提出面向风电叶片复合材料的微波热成像缺陷定量检测方法。在此基础上，阐明微波热成像缺陷检测的理论，建立复合材料内部缺陷的深度定量检测方法和基于自适应稀疏矩阵的缺陷自动分离和面积定量方法，为风电叶片的质量控制和在役检测提供一种直观而高效的手段。