Abstract

Image processing algorithms based on time-frequency analysis are frequently used in testing and researching the mechanical properties of high-temperature materials, especially in aerospace, engines, and ships. However, due to the complexity of the high temperature environment itself, there are many factors that affect the measurement accuracy, among which the existence of thermal airflow disturbance has a particularly significant impact on the digital image correlation method. This paper mainly focuses on two aspects of high temperature edge detection and digital image correlation. On the one hand, the existing algorithm is improved to make it suitable for material property detection in high temperature environment. And relevant experiments are carried out to verify the feasibility and accuracy of the algorithm. The full-field coefficient caching method for fitting initial values proposed in this paper has the premise that the accuracy is comparable to that of the reverse combined Gauss-Newton matching algorithm, but the running speed is improved by about 10%, and the matching accuracy of both is obviously higher than that of the surface fitting algorithm.

摘要

基于时频分析的图像处理算法经常用于高温材料力学性能的测试和研究，特别是在航空航天、发动机和船舶等领域。但由于高温环境本身的复杂性，影响测量精度的因素较多，其中热气流扰动的存在对数字图像相关法的影响尤为显着。本文主要研究高温边缘检测和数字图像相关性两个方面。一方面，对现有算法进行改进，使其适用于高温环境下的材料特性检测。并进行了相关实验验证了算法的可行性和准确性。