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《Journal of Mechanical Engineering》 2009-07
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Distortion Correction Method Based on Mathematic Model in Machine Vision Measurement System

CHEN Ruwen1, 2 HUANG Ren1 ZHANG Zhisheng1 SHI Jinfei1 CHEN Zixin1 (1. School of Mechanical Engineering, Southeast University, Nanjing 211189; 2. Department of Vehicle Engineering,Nanjing Institute of Technology, Nanjing 211167 )  
It is necessary to correct the nonlinear distortions in images of the machine vision measurement system which are vital to measuring precision. The method adopting a time-unvarying parameter model to correct the image distortions is difficult to achieve precise workpiece dimensions due to the stochastic variation of the distortions in production process. So a new nonlinear distortion correction method is proposed. The target part edge data series is described by a general expression for the linear and nonlinear auto-regressive time series model (GNAR model) and with the least square method and the minimum loss function criteria integrated with the computational complexity, the parameter estimation and order determination is realized. The distortion-free edges are obtained after model filtering and the workpiece dimensions are calculated through the vertical distances of the distortion-free edges. Experimental results show that the algorithm can be applied to machine vision measurement system for on-line measurement in machining process.
【Fund】: 国家高技术研究发展计划(863计划)(2006AA040202);; 江苏省科技成果转化项目(BA2006068)资助项目
【CateGory Index】: TP391.41
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