目前, 辅助激光视觉测量法已广泛应用于大型零部件的三维形面测量。针对该方法在测量过程中普遍存在的轮廓边界信息获取不准确的问题, 提出一种面向大型零部件的三维形面测量方法以获得精确的形面信息和轮廓边界信息。首先, 根据光条图像序列采集特性, 基于时间流的光条自适应定位方法实现了光条所在区域的实时定位; 其次, 提出了一种基于光条几何特征突变的边界提取方法, 获取光条处的被测物边界行(列)坐标位置; 然后, 利用光条区域内快速提取的光条中心结果, 确定准确的边界特征点坐标, 并仅保留边界特征点以内的有效光条中心点; 最后, 对所提取的有效光条中心进行了三维重建, 结合光条扫描实现了整个形面的三维快速测量。实验验证结果表明: 该方法可实现被测物三维形面信息的高精度快速测量, 同时获取精确的轮廓边界信息, 其测量精度达到0.06 mm, 且大大减小运算量, 满足大型零部件的快速高精度测量要求。

The measurement method based on laser-aided machine vision has been widely used in 3D shape measurement for large-scale components and parts at present. To solve the problem of the inaccurate extraction for components′ boundaries, a high-precision method of 3D shape measurement for large-scale parts was proposed in this paper. Firstly, an adaptive light stripe locating method based on time flow was proposed according to the sequence of acquiring images, by which the region of the light stripe can be located in real time. Next, a boundary detection method based on light stripe mutations was presented to acquire the row or column coordinates of the object boundaries in the light stripe. Then the coordinates of the boundaries can be determined precisely combined with the extraction results of light stripe centers. And the effective light stripe centers for measurement within the two determined boundary feature points can be retained. At last, the extracted light stripe centers were matched and reconstructed to accomplish 3D shape measurement. Experiment results show that the measurement accuracy of this method reaches 0.06 mm and precise boundary information of objects can be acquired. The cost of computation is also reduced greatly. Thus, the proposed method can satisfy the measurement requirements of high precision and rapid speed.