基于锁相红外方法的纤维增强复合材料深层缺陷检测研究

Comparing with traditional metal materials, fiber reinforced composites with excellent weight rate, strength rate and corrosion resistance behavior, are widely used in aviation and aerospace field. Then as remarkable fabrication process and significant anisotropy, it's mechanisms of damage and failure modes are complicated and diversity. So the damage detection of fiber reinforced composites is more difficult. General no-destructive testing (NDT) methods of aviation fiber reinforced composites, with different advantage, but still are short of applicable special environment, time consumption and not suitable for large size parts, especially the detecting depth is limited, that can't adapt to the requirement of the aviation maintenance project. This study intends to adopt the modulation frequency (FM) ultrasound or heat sources as excitation source, using lock-in infrared thermography as infrared nondestructive testing method, to detect the damage of prefabricated defects and damages of the fiber reinforced composite materials. with the advantage of directly heating of defect location of ultrasonic and relation between frequency and relation of thermal diffusion distance in this method, realizing the identification of deep defect (about 5 mm from surface). Including theoretical analysis the relation between of image sequence and frequency domain, research on processing algorithm of infrared image sequence and defect quantitative evaluation method. Order to realizing accurate detection and quantitative analysis of fiber reinforced composite material defects.

纤维增强复合材料与传统金属材料相比，具有独特的综合力学性能，在航空领域具有广阔的应用前景。但由于特殊的制备工艺以及各向异性特征，复合材料在损伤、失效等方面表现为机理复杂、模式多样，导致判断与检测困难。目前用于现代飞机复合材料的红外无损检测方法虽然各有所长，但缺陷检测深度有限，难以满足现代航空维修工程高效准确的应用需要。本研究拟分别采用调制幅值的超声波或调制频率的热光源作为激励源，锁相技术的红外无损检测方法，对预制缺陷的纤维增强复合材料进行损伤检测。该方法利用了超声激励对缺陷位置直接加热以及热波频率与探测深度存在关联的技术特点，从而实现对复合材料层压板深层（~5mm）缺陷信息的提取。拟从相位图像与频率域的理论、红外图像序列的锁相处理算法以及缺陷的定量评估方法等方面展开研究，从而实现纤维增强复合材料缺陷的准确检测和定量分析。

纤维增强复合材料与传统金属材料相比，具有独特的综合力学性能，在航空领域具有广阔的应用前景。但由于特殊的制备工艺以及各向异性特征，复合材料在损伤、失效等方面表现为机理复杂、模式多样，导致判断与检测困难。目前用于现代飞机复合材料的红外无损检测方法虽然各有所长，但缺陷检测深度有限，难以满足现代航空维修工程高效准确的应用需要。本研究拟分别采用调制幅值的超声波或调制频率的热光源作为激励源，锁相技术的红外无损检测方法，研制出了锁像红外无损检测样机，集成了Matlab 图像降噪算法和目标识别算法。该样机利用了超声激励对缺陷位置直接加热以及热波频率与探测深度存在关联的技术特点，从而实现对复合材料层压板深层缺陷信息的提取。本研究作为民航联合基金，在兼顾算法研究的技术上，侧重系统硬件和软件的高度集成，为国产高性能检测设备的产业化实现提供重要的借鉴意义。