基于视觉的位移和振动测试方法大多需要人工在结构表面预设物理标记, 这使得现场测试和监控变得繁琐。针对现有机器视觉技术在薄壁件振动模态测试上的不足, 提出基于曲率尺度空间(CSS)角点检测与匹配的薄壁件振动模态测试方法。该方法通过人工设置的虚拟角点代替传统的物理标记, 利用改进的CSS角点检测方法定位振动图像序列中的关键点, 并采用基于像素平方差改进的匹配方法实现关键点匹配, 最终获取振动信息并识别模态参数。对薄壁梁和薄壁圆筒进行振动模态实验, 并利用有限元仿真和加速度传感器进行分析验证, 结果表明, 该方法能够有效准确地获得薄壁件的模态参数, 测试精度误差在5%以内。

Most of the displacement and vibration testing methods based on vision require artificial marker on structure surface, which makes vision-based testing and monitoring for real-life more complicated. Aiming at the disadvantages of the existing machine vision technology in vibration modal testing for thin-walled components, a vibration modal testing method of thin-walled components based on curvature scale space (CSS) corner detecting and matching is proposed. The virtual corner is set to replace traditional physical targets, and the key point of vibration image sequence of thin-walled components is oriented by the improved CSS corner detection algorithm, which is matched by using. Thus, the vibration information is obtained and modal parameters are identified. Eventually, the vibration modal testing experiments for thin-walled beam and thin-walled cylinder is carried out. By analyzing measurement results and verifying with finite element simulation and accelerometer, the results show that the proposed method can effectively and accurately obtain modal parameters, and the measurement error is less than 5%.