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机构地区:[1]南通大学,江苏南通226019
出 处:《工程图学学报》2011年第3期23-27,共5页Journal of Engineering Graphics
基 金:南通市应用研究计划资助项目(K2009022);江苏省高校自然科学基础研究资助项目(07KJD540178)
摘 要:在孔组复合位置度误差评判过程中,用传统的数值优化方法一般难以找到符合最小条件判别准则的几何图框理想位置,尤其当位置度公差遵守最大实体要求且被测要素尚未达到最小实体尺寸时,被判为不合格的零件还有被修复的可能。针对上述问题,可利用自适应遗传算法全局搜索几何图框最佳位置,并在搜索过程中同时考虑遵守最大实体要求时的误差补偿因素的影响。此外,针对不合格零件进行的可修复性判别和修正量的计算,进一步降低了零件误废率。In the evaluating process of hole group composite position error,the traditional numerical optimization methods are generally difficult to find an ideal location for the geometric frame to meet the minimum condition criterion,especially when the position tolerance follows the principle of MMC and the measured features still do not reach the minimum material size,parts judged unqualified may also be repaired.Aiming at solving the above-mentioned problems,the adaptive genetic algorithm is proposed to search the best location for geometric frame globally,and at the same time,the error compensation due to following MMC principle is taken into account while searching.In addition,the repair-ability judgment and correction calculation are also carried out against failed parts,which will further reduce the false rejection.
分 类 号:TH161[机械工程—机械制造及自动化]
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