MINIMAL WORST CASE OPTIMAL SAMPLING FOR SYSTEMATIC ANGULAR ERROR IDENTIFICATION IN MULTI-AXIS CNC MACHINE TOOLS

摘要：

A new method for identifying systematic errors in multi-axis CNC machine tools is presented. The minimal worst case estimate of the parameters of degrees m, n dimensional polynomials is given. The angular errors polynomials are the sum of n monomials in degrees m. The optimal sampling schedule for this case is found. Based on optimal sampling points and workspace of machine tool an artifact is designed for drilling holes. The procedure to measure i, j, k values of the artifact holes on a CMM is developed. A case study identifying the angular error of and X Z C CNC lathe illustrates the theory. The systematic angular errors of the case study machine tools were modeled as three dimensional polynomials of degree 5 based on 142 optimal sampling points.

关键词： Multi-azis CNC systematic error optimal sampling Minimal Worst Case.

作者: N. V. Chung G. Belforte Erik L. J. Bohez

作者单位: Asian Institute of Technology, Thailand Politechnico Di Torino, Italy

会议类型: 国际会议

会议名称: 第二十届国际生产研究大会

会议地点: 上海

会议语种:英文

页码: 1-7

在线出版日期: 2009-08-02（万方平台首次上网日期，不代表论文的发表时间）