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Improvement of high-temperature deformation measurement accuracy based on image restoration method

机译:基于图像恢复方法的高温变形测量精度提高

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摘要

Digital image correlation (DIC) is a full-field and non-contact technique based on white-light illumination for displacement and strain measurement. Because of these advantages, it can be used to measure the mechanical properties of materials at high temperature. However, there are still many urgent matters to be solved in using the DIC method in high-temperature measurement, such as the heat flow disturbance. This can warp the images acquired in high temperatures and cause a tiny move of the images acquired at the same temperature, even making the gray value of the images change, so the results of the measurement will not be guaranteed. This paper proposes a method to reduce these influences and improve the accuracy of high-temperature measurement results. Degraded images can be processed by using a combination of the image inverse filter method and an image averaging algorithm. Then the processed images can be used to calculate the displacement and strain. The experimental results show that using an image inverse filter and image averaging algorithm to process images can produce smaller RMS errors and more stable results than the values calculated from the original images with no processing. Using this method can improve the accuracy of high-temperature measurement.
机译:数字图像相关(DIC)是基于白光照射的全场和非接触技术,用于位移和应变测量。由于这些优点,它可用于测量高温材料的机械性能。然而,在高温测量中使用DIC方法仍有许多迫切要求解决,例如热流扰动。这可以经过高温获取的图像并导致在相同温度下获取的图像的微小移动,甚至使图像的灰度值改变,因此不会得到保证测量结果。本文提出了一种减少这些影响的方法,提高高温测量结果的准确性。可以通过使用图像逆滤波方法和图像平均算法的组合来处理劣化的图像。然后,处理的图像可用于计算位移和应变。实验结果表明,使用图像逆滤波器和图像平均算法来处理图像可以产生较小的RMS错误,并且比从没有处理的原始图像计算的值更稳定的结果。使用该方法可以提高高温测量的准确性。

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