基于双目视觉的数控机床动态轮廓误差三维测量方法

doi:10.3901/JME.2019.10.001

机械工程学报 ›› 2019, Vol. 55 ›› Issue (10): 1-9.doi: 10.3901/JME.2019.10.001

• 仪器科学与技术 • 下一篇

基于双目视觉的数控机床动态轮廓误差三维测量方法

刘巍, 李肖, 李辉, 潘翼, 贾振元

大连理工大学机械工程学院大连 116024

收稿日期:2018-07-13 修回日期:2019-03-10 出版日期:2019-05-20 发布日期:2019-05-20
通讯作者: 刘巍(通信作者),男,1979年出生,博士,教授,博士研究生导师。主要研究方向为精密测量控制、微执行器、机床误差测量等。E-mail:lw2007@dlut.edu.cn
作者简介:李肖,男,1989年出生,博士研究生。主要研究方向为机器视觉,基于视觉的机床轮廓误差检测等。E-mail:melixiao@mail.dlut.edu.cn
基金资助:
国家自然科学基金优秀青年科学基金（51622501）、大连市高层次人才创新计划（2017RJ04）、NSFC—辽宁联合基金和创新研究群体科学基金（51321004）资助项目

Binocular Vision-based Three-dimensional Contouring Error Calibration Method for NC Machine Tools

LIU Wei, LI Xiao, LI Hui, PAN Yi, JIA Zhenyuan

School of Mechanical Engineering, Dalian University of Technology, Dalian 116024

Received:2018-07-13 Revised:2019-03-10 Online:2019-05-20 Published:2019-05-20

摘要/Abstract

摘要： 轮廓误差是评估数控机床动态性能的重要指标。定期检测和标定数控机床动态轮廓误差对于稳定机床加工精度至关重要。针对采用现有单一测量手段所测的动态轮廓误差轮廓范围小、维数低、轨迹形式受限等问题，提出基于双目视觉的机床轮廓误差测量方法，实现数控机床任意轨迹轮廓误差三维高精度测量。具体包括设计基于高精度强化特征和高均匀光照的便携式合作靶标以准确表征机床运动位置信息，实现靶标与工作台的高精度安装以及强化特征的高质量成像；利用偏心补偿算法准确定位强化特征图像二维位置，解决圆型强化特征成像仿射畸变为椭圆问题，提高图像处理与机床位置的视觉定位精度；提出基于相机成像全局建模的测量基准位姿变换方法，准确完成数据转换并求解机床轮廓误差。以五轴数控机床平面插补的三叶玫瑰轨迹为研究对象，搭建轮廓误差视觉测量系统并开展测量试验。以平面光栅测量结果为标准验证视觉求解精度。结果表明，在1 500 mm/min进给速度下视觉轮廓误差求解误差为9.79 μm，平均测量误差为3.36 μm。

关键词: 机床误差, 轮廓误差, 双目视觉, 图像处理, 五轴数控机床

Abstract: Contouring error is a key indicator for evaluating the dynamic characteristic of NC machine tools. Accurate periodic assessment of contouring error of machine tools guarantees the improvement of the machine tool manufacturing precision. To overcome the limitations of measurement range, measurement dimensions and measurement trajectory forms of the existing measurement equipment, a binocular vision-based three-dimensional contouring error calibration system and method is proposed, realizing the three-dimensional error measurement of an arbitrary trajectory in conditions of wide motion range. First, a cooperative target with high uniform illumination and high-precision enhancement marker is designed and then installed on the workbench, in which the circle marker which can be imaged with high quality is utilized to characterize the movement position of NC machine tools. Then, an eccentricity compensation algorithm is implant to calculate the position of the marker in image coordinate frame, solving the circular affine distortion in image processing. Thereafter, a data transformation method based on global modeling of camera imaging is proposed, and the three-dimensional coordinate of the marker are constructed and converted into the machine tool coordinate frame. Finally, the contouring error can be calculated by comparing the measurement curve with nominal curve. Experiments for the detection of contouring error of three-leaved rose curve is performed in a self-established five-axis machine tool. The feasibility and accuracy of the proposed vision measurement method are verified by the cross grid-encoder. The results show that the maximum error of vision measurement method for a feed rate of 1 500 mm/min is 9.97 μm and the average measurement error is 3.36 μm.

Key words: binocular vision, contouring error, five-axis machine tool, image processing, machine tool errors

中图分类号:

刘巍, 李肖, 李辉, 潘翼, 贾振元. 基于双目视觉的数控机床动态轮廓误差三维测量方法[J]. 机械工程学报, 2019, 55(10): 1-9.

LIU Wei, LI Xiao, LI Hui, PAN Yi, JIA Zhenyuan. Binocular Vision-based Three-dimensional Contouring Error Calibration Method for NC Machine Tools[J]. Journal of Mechanical Engineering, 2019, 55(10): 1-9.

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基于双目视觉的数控机床动态轮廓误差三维测量方法

Binocular Vision-based Three-dimensional Contouring Error Calibration Method for NC Machine Tools

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