...
首页> 外文期刊>Precision Engineering >Methods for evaluation of systematic geometric deviations in machined parts and their relationships to process variables
【24h】

Methods for evaluation of systematic geometric deviations in machined parts and their relationships to process variables

机译:评估机械零件中系统几何偏差及其与过程变量的关系的方法

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Increasing demands for precision-machined parts put a greater emphasis on achieving a better understanding of the relationships between manufacturing process variables and deviations from perfect geometric forms. To achieve this understanding, itis important to have high-quality metrology data on part features, which (in some sense) span the range of variability in form for the process under study. The problem is complex, involving the machine tool itself, materials, fixtures, cutters, feeds,speeds, and many other factors. In this report, a method is introduced that can identify key deviations from perfect form and can elucidate their dependence on some of the factors enumerated above. This work presents two useful models for form errors ofcylindrical features and develops special cases of those models to suit specific requirements. One is an analytical model based on Chebyshev polynomials to model the axial errors and Fourier series to model angular dependencies. The second modelingapproach uses the techniques of principal component analysis to extract a basis set of characteristic shapes directly from the measurement data. This report includes a full development of the mathematical basis for the analysis and concludes with someapplication examples.
机译:对精密加工零件的需求越来越大,这更加强调了对制造过程变量与偏离完美几何形状之间的关系的更好理解。为了获得这种理解,重要的是要获得零件特征的高质量计量数据,从某种意义上说,该数据在某种程度上跨越了所研究过程的形式变异性范围。问题很复杂,涉及机床本身,材料,固定装置,刀具,进给,速度和许多其他因素。在此报告中,介绍了一种方法,该方法可以识别与完美形式的关键偏差,并可以阐明它们对上面列举的某些因素的依赖性。这项工作提出了两个有用的模型,用于圆柱形状的形状误差,并开发了这些模型的特殊情况以适合特定的要求。一种是基于Chebyshev多项式的分析模型来对轴向误差建模,而傅立叶级数则用于对角度依赖性建模。第二种建模方法使用主成分分析技术直接从测量数据中提取特征形状的基础集。该报告包括用于分析的数学基础的完整开发,并以一些应用示例作为结尾。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号