空间柔性绳索在航天航空领域有着广泛的应用，柔性绳索具有结构大、刚度低、大变形的特t点，在做大范围运动时位移、转动与弹性变形相互耦合，增大了其动力学建模的难度。为验证柔性绳索动力学模型的准确性，采用非接触式的视觉测量方法进行实验验证，利用背景建模、差分、平滑与二值化一系列图像预处理方法提取绳索目标区域，并基于距离变换的多尺度连通骨架算法计算出绳索中心线，通过求解相机外参数矩阵计算出绳索中心线的平面位置。由于柔索自身灰度均匀，图像特征不明显，无法对绳索上特定位置进行跟踪，现有方法都在测量对象上粘贴或喷涂特征点，对于质量轻、弯曲刚度小的柔索，这种方法会影响柔索自身的动力学特性，因此提出一种适应绳索弯曲及纵向弹性形变的物质点跟踪算法，能够不借助外加特征的情况下，对绳索上任意给定物质点进行跟踪计算。以基于绝对节点坐标方法建立的柔索动力学模型为例验证其模型的准确性，结果表明，该绳索动力学模型仿真结果与实验结果具有较强的一致性。相比于其他测量方法，物质点跟踪算法能够降低柔索测量过程中的外干扰因素，为动力学模型验证提供准确的实验参考结果。

The flexible cable is widely applied in the field of astronautics and aeronautics, and has the characteristics of large structure, low rigidity and large deformation. In large range motion, the displacement, rotation and elastic deformation of the flexible cable are coupled with each other, increasing the difficulties in dynamic modeling of the flexible cable. To verify the accuracy of the dynamic model for the flexible cable, the non-contact visual measurement method is used. The movement area of the cable is extracted by a series of image preprocessing methods, such as background modeling, and image difference, smoothing and binarization. The cable centerline is obtained by the hierarchical-connected skeletonization algorithm based on distance transform, and the planer position of the centerline is calculated by solving the camera external matrix. With even gray level, the cable does not have obvious image characteristics, making it difficult to track a specific point of the cable. In the previous methods, the feature point on the cable is pasted or sprayed, affecting the dynamic characteristics of the flexible cable. A material point tracking algorithm which can adapt to the bending and longitudinal elastic deformation of the flexible cable is proposed. The algorithm can be used to track any point of the cable without additional features. The dynamic model for the flexible cable is built based on the absolute nodal coordinate formulation, and the simulation results are consistent with the experimental results. Compared with other measurement methods, the material point tracking algorithm can reduce the factors of external interference in the measurement process, providing accurate experimental reference results for dynamic model verification.