金属增材制造内部缺陷激光热波检测方法研究

Study on laser infrared thermography for detecting subsurface defects in metal additive manufacturing

金属增材制造是近年来发展迅速的一种高效材料加工技术,为了保障构筑件的质量和可靠性,应避免其内部形成对结构力学性能有显著影响的缺陷。本文研究了激光红外热成像检测技术在金属增材制造亚表面缺陷检测上的应用。首先,基于有限元仿真结果,研究了激光红外热成像检测对不同深度和尺寸的金属亚表面缺陷检测的可靠性,进一步地,考虑了粗糙表面对检测的影响,并对比验证了常用红外热成像序列处理算法的噪声干扰抑制性能;最后,对加工有人工内部缺陷的选择性激光熔融试件进行了实验验证。仿真和实验结果表明,激光红外热成像检测可以可靠地检出宽深比大于1的金属增材制造内部亚表面缺陷,通过常用的热成像序列预处理方法,可以有效地抑制粗糙表面干扰造成的空间噪声,此外,由于激光红外热成像检测技术具备高效、非接触以及可视化的优势,有望成为金属增材制造在线监测的可靠技术。

Metal additive manufacturing is a rapidly developing high-efficiency material processing technology in recent years.In order to ensure the quality and reliability of fabricated parts,the formation of defects within them that have a significant impact on the mechanical properties of the structure should be avoided.In this paper,the application of laser infrared thermography for detecting subsurface defects in metal additive manufacturing is investigated.Firstly,based on finite element simulation results,the reliability of laser infrared thermography for detecting subsurface defects of different depths and sizes in metal additive manufacturing is studied.Furthermore,the influence of rough surfaces on detection is taken into account,and the noise suppression performance of commonly used infrared thermography sequence processing algorithms is comparatively verified.Finally,Experimental validation of the processing of selective laser melting specimens with artificial internal defects is carried out.The simulation and experimental results demonstrate that laser infrared thermography can reliably detect the internal sub-surface defects of metal additive manufacturing with a width-to-depth ratio greater than 1 and the spatial noise caused by rough surface interference can be effectively suppressed by the commonly used pre-processing method of thermography sequences.In addition,laser infrared thermography inspection is expected to be a reliable technology for online monitoring of metal additive manufacturing due to its advantages of high efficiency,non-contact and visualization.