深度引导的DIC用于3D形状,变形和不连续表面上的应变测量
Optics express
|August 13, 2025
概括
一种新的深度引导数字图像相关性 (DIC) 方法准确地测量了不连续表面的3D变形和应变. 这种技术克服了复杂几何形状的传统DIC的局限性,提高了结构和生物启发工程的精度.
科学领域:
- 工程 工程师 工程师 工程师
- 材料科学 材料科学 材料科学
- 光学是什么?光学是什么?光学是什么?
背景情况:
- 数字图像相关性 (DIC) 是一种基于视觉的关键技术,用于测量变形和应变.
- 传统的DIC方法与不连续的表面作斗争,导致由于形状描述不准确而导致偏差的测量.
研究的目的:
- 使用DIC.开发一个准确的3D测量方法,用于不连续的表面.
- 为了提高复杂几何形状的变形和应变分析的精度.
主要方法:
- 提出了一种深度引导的DIC方法,将图像变形与3D对象形状联系起来.
- 边缘投射特征测量 (FPP) 用于捕获详细的3D表面数据.
- 一个新的策略涉及分裂和再生子集用于代的DIC计算.
主要成果:
- 该方法准确地捕捉了不连续表面的3D形状,变形和应变.
- 发现匹配错误与物体的3D几何直接相关.
- 在位移和应变场分析准确度方面取得了显著的改进.
结论:
- 深度引导的DIC方法为复杂的表面提供了准确的3D测量.
- 这种技术在结构力学和生物启发工程中具有宝贵的应用.
- 它克服了标准DIC对具有突然几何变化的对象的局限性.
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