Burr detection by using vision image

In this paper, a practical force model for the deburring process is first presented. It will be shown that the force model is more general than Kazerooni's model and it is suitable for both upcut and down-cut grinding. In terms of this force model, an algorithm of burr detection by using a 2D vision image is proposed. In the burr detection algorithm, the relevant data of burrs, such as frequency, cross-section area, and height are simplified so that they are functions of the burr contour only. Then, a fast tracking method of the burr contour (BCTM) is developed to obtain the contour data. Experiments show that the BCTM of this passive (i.e. without lighting) image system can be as fast as 18.2 Hz and its precision is 0.02 mm, so online burr detection and control by using the vision sensor is feasible.

[1]  Azriel Rosenfeld,et al.  Digital Picture Processing , 1976 .

[2]  Azriel Rosenfeld,et al.  A Note on the Use of Local MIN and MAX Operations in Digital Picture Processing , 1977 .

[3]  Robert M. Haralick,et al.  Gradient threshold selection using the facet model , 1988, Pattern Recognit..

[4]  H. Harry Asada,et al.  Optimal compliance design for grinding robot tool holders , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[5]  G. Boothroyd,et al.  Fundamentals of Metal Machining and Machine Tools , 1975 .

[6]  M. M. Sadek,et al.  A New Approach to Development of a Grinding Force Model , 1987 .

[7]  松尾 哲夫,et al.  Fundamentals of Metal Machining and Machine Tools, G. Boothroyd, Scripta Book Company, 1975 , 1984 .

[8]  C. E. Davis.  The dependence of grinding wheel performance on dressing procedure , 1974 .

[9]  R. Lindsay.  Principles of Grinding , 1986 .

[10]  C. S. G. Lee,et al.  Robotics: Control, Sensing, Vision, and Intelligence , 1987 .

[11]  A. D. Brink,et al.  Grey-level thresholding of images using a correlation criterion , 1989, Pattern Recognit. Lett..

[12]  M. M. Sadek,et al.  Theoretical Analysis of Grinding Chatter , 1987 .

[13]  T. W. Ridler,et al.  Picture thresholding using an iterative selection method. , 1978 .

[14]  Azriel Rosenfeld,et al.  A Threshold Selection Technique , 1974, IEEE Transactions on Computers.

[15]  John F. Haddon,et al.  Generalised threshold selection for edge detection , 1988, Pattern Recognit..

[16]  C. Rubenstein.  The mechanics of grinding , 1972 .

[17]  Eliezer L. Lozinskii,et al.  Semantic thresholding , 1987, Pattern Recognit. Lett..

[18]  R. S. Hahn,et al.  On the Mechanics of the Grinding Process Under Plunge Cut Conditions , 1966 .

[19]  Homayoon Kazerooni,et al.  An Approach to Automated Deburring by Robot Manipulators , 1986 .

[20]  Daniel E. Whitney,et al.  Development and Control of an Automated Robotic Weld Bead Grinding System , 1990 .

[21]  Homayoon Kazerooni,et al.  Automated roboting deburring using electronic compliancy; Impedance control , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.