Ice detection is an important issue in the field of icing prevention and de-icing. In this study, an experimental platform was built for ice detection using flash pulse infrared thermal wave detection, followed by a quantitative recognition approach for identifying the three-dimensional shape of ice. The new method was combined the edge recognition with thickness calculation of inverse heat transfer problem. And the edge of the ice was based on the Principal Component Analysis (PCA) and the Canny algorithm. Thus, by processing the ice edges and giving an initial thickness, the finite element model of the ice was established to numerically simulate the temperature distribution for ice thickness inversion based on the forward heat transfer problem. Meanwhile, the thickness of the ice was inversed by the Levenberg-Marquardt (LM) method based on the inverse heat transfer problem. The resulting edges and thickness of the ice were found to be in good agreement with the experimental results, demonstrating the feasibility of the proposed methods. This paves the way to explore an effective accurate and quantitative identification method for three-dimensional ice shape detection in infrared thermal wave detection.

结冰检测是防冰除冰领域的一个重要课题。本研究建立了一个利用闪光脉冲红外热波探测进行冰检测的实验平台，然后采用定量识别方法识别冰的三维形状。新方法将边缘识别与反传热问题的厚度计算相结合。冰的边缘基于主成分分析（PCA）和 Canny 算法。因此，通过处理冰的边缘并给出初始厚度，建立冰的有限元模型，以数值模拟基于正传热问题的冰厚度反演的温度分布。同时，冰的厚度通过基于逆传热问题的 Levenberg-Marquardt (LM) 方法进行反演。结果发现冰的边缘和厚度与实验结果非常吻合，证明了所提出方法的可行性。这为探索红外热波探测中三维冰形探测的有效准确定量识别方法铺平了道路。