High-speed measurement algorithm for the position of holes in a large plane

Abstract CMM is widely used to measure the position of the holes on the top surface of an engine block. However, CMM requires a perfect environment and cannot be applied in online measurements. Moreover, using CMM to measure the position of holes in a large plane takes more than 10 min, thus lowering its efficiency. To solve this problem, this paper presents a high-speed measurement algorithm for the position of holes in a large plane based on a flexible datum and the feature neighborhood model. First, two area CCD cameras that grab the images of the reference holes of the block are used to establish the flexible datum. Second, different mapping models are built in the neighborhood of the center of different holes. These black-box mapping models ignore the intermediate process of camera perspective projection. Finally, the feature points in the different scales of the neighborhood of the hole centers solve the mapping results. The mapping results are then weighted by using the multi-scale weighting algorithm. The calibration target is designed, but the feature points in the target are minimal. Thus, a new method to create several more feature points is designed. Compared with the measurement result of CMM, the maximum position error of the measurement system is 0.025 mm. The relative error is better than 0.025% and the standard deviation of the measurement data is less than 0.010 mm. With a conference level of 95%, the system measurement uncertainty is better than ±0.020 mm. The measuring time is less than 3 min. The position measurement scheme features high automation and high efficiency, and can be used in the position measurement of online engine block holes.

[1]  R. W. Baines,et al.  A coordinate measuring machine vision system , 1999 .

[2]  Joshua Mutambi,et al.  Application of digital image analysis method in metric screw thread metrology , 2004 .

[3]  S. Standard.  GUIDE TO THE EXPRESSION OF UNCERTAINTY IN MEASUREMENT , 2006 .

[4]  Yeung Sam Hung,et al.  Projective reconstruction of ellipses from multiple images , 2010, Pattern Recognit..

[5]  Naoufel Werghi,et al.  Best ellipse and cylinder parameters estimation from laser profile scan sections , 2012 .

[6]  Reuven Katz,et al.  Integration of reconfigurable inspection with stream of variations methodology , 2005 .

[7]  Satoshi Kiyono,et al.  A dual-mode surface encoder for position measurement , 2005 .

[8]  S. V. Kosarevsky,et al.  Practical Procedure for Position Tolerance Uncertainty Determination via Monte-Carlo Error Propagation , 2012 .

[9]  W. Gander,et al.  Fitting of circles and ellipses: Least squares solution , 1994 .

[10]  Y. S. Tarng,et al.  An auto-alignment vision system with three-axis motion control mechanism , 2005 .

[11]  W. Gander,et al.  Fitting of circles and ellipses least squares solution , 1995 .

[12]  Ralf Reulke,et al.  Determination and improvement of spatial resolution of the CCD-line-scanner system ADS40 , 2006 .

[13]  Fang-Jung Shiou,et al.  Development of a novel scattered triangulation laser probe with six linear charge-coupled devices (CCDs) , 2009 .

[14]  Carlos Ricolfe-Viala,et al.  Correcting non-linear lens distortion in cameras without using a model , 2010 .

[15]  Jose Mathew,et al.  Effect of CMM point coordinate uncertainty on uncertainties in determination of circular features , 2006 .

[16]  Guangjun Zhang,et al.  Large 3D free surface measurement using a mobile coded light-based stereo vision system , 2006 .

[17]  John S. Agapiou,et al.  Machining Quality Analysis of an Engine Cylinder Head Using Finite Element Methods , 2003 .

[18]  Ming Xu,et al.  Tracking the soccer ball using multiple fixed cameras , 2009, Comput. Vis. Image Underst..

[19]  Youfu Li,et al.  A global calibration method for large-scale multi-sensor visual measurement systems , 2004 .

[20]  Sergey Kosarevsky,et al.  Development of an Algorithm to Detect Screw Threads in Planar Point Clouds , 2013 .

[21]  Chern-Sheng Lin,et al.  An image system for fast positioning and accuracy inspection of ball grid array boards , 2001, Microelectron. Reliab..

[22]  Zhijiang Du,et al.  Non-contact Measurement of Damaged External Tapered Thread Based on Linear Array CCD , 2006 .

[23]  Ted Hopp,et al.  The Sensitivity of Three-Point Circle Fitting , 1994 .

[24]  D. Steiner,et al.  Measurement Techniques for the Inspection of Porosity Flaws on Machined Surfaces , 2007, J. Comput. Inf. Sci. Eng..

[25]  Chia-Hsiang Menq,et al.  Automatic camera calibration for a multiple-sensor integrated coordinate measurement system , 2001, IEEE Trans. Robotics Autom..

[26]  Robert Schmitt,et al.  Geometric error measurement and compensation of machines : an update , 2008 .

[27]  Xiaoming Zhang,et al.  Superellipse fitting to partial data , 2003, Pattern Recognit..

[28]  S Vishnupriyan,et al.  Optimization of machining fixture layout for tolerance requirements under the influence of locating errors , 2010 .

[29]  Xiangqian Jiang,et al.  Multisensor data fusion in dimensional metrology , 2009 .

[30]  Sergey Kosarevsky,et al.  Practical way to measure large-scale 2D parts using repositioning on coordinate-measuring machines , 2009, 0908.3209.

[31]  Gary C. Lin,et al.  Design and analysis of experiments in CMM measurement uncertainty study , 2007 .