| 基于退化函数优化的高温DIC测量方法 |
| High-temperature DIC measurement method based on degradation function optimization |
| 投稿时间：2025-04-07 修订日期：2025-04-29 |
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| 中文摘要: |
| 为解决高温热气流扰动下散斑图像模糊与噪声耦合导致的数字图像相关（Digital Image Correlation, DIC）测量精度下降问题，运用图像退化理论与多帧信号处理理论，采用退化函数参数优化与灰度平均相结合的方法，通过构建基于结构相似性（Structural Similarity , SSIM）的损失函数优化模型进行退化参数（α, β）自适应估计，利用维纳滤波与灰度平均完成去模糊与降噪，突破了传统固定退化模型与实际热扰动不匹配及噪声抑制与细节保留矛盾的难点，最终实现了高图像质量、低失真的散斑图像复原。经600℃高温实验平台验证，复原图像的图像质量得到明显提升，DIC 位移测量均方根误差（Root Mean Square Error，RMSE）降至 0.065 mm，能够有效满足高温环境下材料变形测量亚像素级精度的要求，为推动DIC技术在极端工况测试领域的实用化发展起到关键支撑作用。 |
| 英文摘要: |
| In order to solve the problem of digital image correlation (DIC) measurement accuracy decline caused by the coupling of speckle image blur and noise under high temperature hot air disturbance, the image degradation theory and multi-frame signal processing theory are used, the degradation function parameter optimization and grey release average are combined, and the degradation parameters (α, β) are self-adaptive estimated by constructing a loss function optimization model based on structural similarity (SSIM). Wiener filtering and grayscale averaging are used to complete deblurring and noise reduction, breaking through the traditional fixed degradation model and the actual thermal disturbance mismatch and the contradiction between noise suppression and detail preservation. Finally, high image quality and low distortion speckle image restoration are realized. After being verified by the 600°C high-temperature experimental platform, the image quality of the restored images has been significantly improved, and the root mean square error (RMSE) of DIC displacement measurement has been reduced to 0.065 mm, which can effectively meet the requirements of sub-pixel accuracy in material deformation measurement under high temperature environments. It plays a key supporting role in promoting the practical development of DIC technology in the field of extreme working conditions testing. |
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| 中文关键词: 热扰动 退化函数优化 灰度平均 数字图像相关 |
| 英文关键词:thermal disturbance degradation function optimization grayscale averaging DIC |
| 基金项目:国家自然科学基金项目(62275059)；黑龙江省自然基金项目(YQ2023F014)；中央高校基本科研业务项目(3072024XX0807)；精密测试技术及仪器全国重点实验室开放课题(2024PMTI03) |
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