摘要
为实现车用电池顶盖等有平面特征的工件局部平面度在线检测,提出一种基于点云的局部平面度检测方法。首先用激光传感器获取目标点云,经聚类算法提取工件主平面法向量,根据法向量提供的倾角信息,对点云进行旋转,使点云倾角得到校正。然后,将旋转后的点云转换为灰度图,将其与标准灰度图进行模板匹配,获取待测件与标准件间的平移量和偏转角,完成点云校准。从已校准点云的指定区域截取点集,用最小二乘法进行平面度估计。该方法分别与迭代最近点法(ICP)以及三坐标测量机进行了电池顶盖平面度测量的对比实验。三者测量结果总体一致,但该法在耗时上至少减少62%。作为一种结构简单、高效可靠的技术手段,该方法在精密制造领域具有广泛的应用前景和参考价值。
To realize on-line detection of local flatness of workpieces with planar features(e.g., cap of power battery), a flatness detection method based on point cloud is proposed. First, the point cloud is acquired by a 3D laser-scanning sensor, and the unit normal vector of the main plane in the workpiece is achieved by a clustering algorithm. The point cloud is rotated to fulfill tilt of the point cloud alignment. Then, the rotated point cloud is transformed into a grayscale image. Template matching is performed with the grayscale image of the standard workpiece to obtain the offset angle and deflection angle between the measured workpiece and the standard workpiece. In this way, the point cloud is calibrated. A point set is intercepted from the aligned point cloud in a given region, and the flatness estimation is implemented using the least square method. The proposed method is applied to the online flatness detection of the automotive battery terminal plate. It is compared with the methods based on the ICP algorithm and the three-coordinate measuring instrument. Experimental results show that the proposed method can save 62% of the time, which also has consistent detection results with two methods. As a simple, efficient and reliable technique, the proposed method has broad application prospects and reference value in the field of precision parts manufacturing.
作者
汪威
张开颜
刘亚川
黄玉春
Wang Wei;Zhang Kaiyan;Liu Yachuan;Huang Yuchun(School of Mechanical Engineering,Hubei University of Technology,Wuhan 430068,China;School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430072,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2020年第2期218-225,共8页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(61976083)项目资助.
关键词
电池顶盖
平面度检测
点云
混合校准法
power battery cap
flatness detection
point cloud
hybrid alignment method
作者简介
通信作者:汪威,2006年于湖北工业大学获得硕士学位,2012年于华中科技大学获得博士学位,现为湖北工业大学讲师,主要研究方向为机器视觉、机器人视觉引导、人工智能及其工业应用。E-mail:Alvin_wangw@163.com;张开颜,2017年于湖北工业大学获得学士学位,现为湖北工业大学硕士研究生,主要研究方向为机器视觉、图像处理和人工智能。E-mail:zkyv6@qq.com
