Determine a vision system's 3D coordinate measurement capability using Taguchi methods
暂无分享,去创建一个
Before a machine vision system can be used effectively in a production environment, its capability (accuracy and repeatability) must be determined. In this project, a Taguchi methods-based systematic methodology is used to determine a vision system's three-dimensional (3D) coordinate measurement capability. This methodology reduces the effect of the noise factors rather than removes them which may be costly. Seven factors (i.e., lens type, colour of background, distance between two objects, distance between camera and target, filter, lighting source, and angle between the camera's optic axis and the target's surface) are studied in an L27(313) orthogonal array. The experiment results show that when set up correctly, the selected vision system can measure to 0·004 inch (1 in. = 25·4mm) of accuracy and 0·001 in. of repeatability. The process capability percent and response figures show the amounts of change when the setup factor levels deviate from the optimal one.
[1] Roger Y. Tsai,et al. A new technique for fully autonomous and efficient 3D robotics hand/eye calibration , 1988, IEEE Trans. Robotics Autom..
[2] WILLIAM CHEN,et al. 3-D camera calibration using vanishing point concept , 1991, Pattern Recognit..
[3] Douglas C. Montgomery,et al. Introduction to Statistical Quality Control , 1986 .