In this work, we present a novel approach to photothermal super resolution based thermographic resolution of internal defects using two-dimensional pixel pattern-based active photothermal laser heating in conjunction with subsequent numerical reconstruction to achieve a high-resolution reconstruction of internal defect structures. With the proposed adoption of pixelated patterns generated using laser coupled high-power DLP projector technology the complexity for achieving true two-dimensional super resolution can be dramatically reduced taking a crucial step forward towards widespread practical viability. Furthermore, based on the latest developments in high-power DLP projectors, we present their first application for structured pulsed thermographic inspection of macroscopic metal samples. In addition, a forward solution to the underlying inverse problem is proposed along with an appropriate heuristic to find the regularization parameters necessary for the numerical inversion in a laboratory setting. This allows the generation of synthetic measurement data, opening the door for the application of machine learning based methods for future improvements towards full automation of the method. Finally, the proposed method is experimentally validated and shown to outperform several established conventional thermographic testing techniques while conservatively improving the required measurement times by a factor of 8 compared to currently available photothermal super resolution techniques.
翻译:在这项工作中,我们提出了一个以光热超分辨率为基础的内部缺陷的热解解解方法新颖的方法,即使用二维像素模式的活性光热激光取暖,结合随后的数值重建,实现内部缺陷结构的高分辨率重建;建议采用激光结合高功率DLP投影器技术产生的像素模型,可以大大降低实现真正的二维超分辨率的复杂性,从而朝着广泛实际可行性的方向迈出关键的一步;此外,根据高功率DLP投影器的最新发展,我们提出了内部缺陷的热解解方法,我们提出了对大型金属样品进行结构式脉冲热解检查的首次应用;此外,还提出了对深层反向问题的前瞻性解决办法,同时提出了适当的超热化方法,以找到实验室环境中数字转换所需的正规化参数;这样可以生成合成测量数据,为今后改进方法的机器学习方法打开大门;最后,根据高功率DLP投影投影仪的最新发展,我们试验性地验证并展示了这些方法优于若干既定的常规脉冲学测试技术,同时保守地改进所需的高分辨率测量时间,用现有高分辨率技术比现有高分辨率8的超高分辨率技术。