首页> 外文学位 >Model Agnostic Extreme Sub-pixel Visual Measurement and Optimal Characterization.
【24h】

Model Agnostic Extreme Sub-pixel Visual Measurement and Optimal Characterization.

机译:模型不可知的极端亚像素视觉测量和最佳表征。

获取原文
获取原文并翻译 | 示例

摘要

It is possible in a properly controlled environment, such as industrial metrology, to make significant headway into the non-industrial constraints on image-based position measurement using the techniques of image registration and achieve repeatable feature measurements on the order of 0.3% of a pixel, or about an order of magnitude improvement on conventional real-world performance. These measurements are then used as inputs for a model optimal, model agnostic, smoothing for calibration of a laser scribe and online tracking of velocimeter using video input. Using appropriate smooth interpolation to increase effective sample density can reduce uncertainty and improve estimates. Use of the proper negative offset of the template function has the result of creating a convolution with higher local curvature than either template of target function which allows improved center-finding. Using the Akaike Information Criterion with a smoothing spline function it is possible to perform a model-optimal smooth on scalar measurements without knowing the underlying model and to determine the function describing the uncertainty in that optimal smooth. An example of empiric derivation of the parameters for a rudimentary Kalman Filter from this is then provided, and tested. Using the techniques of Exploratory Data Analysis and the "Formulize" genetic algorithm tool to convert the spline models into more accessible analytic forms resulted in stable, properly generalized, KF with performance and simplicity that exceeds "textbook" implementations thereof. Validation of the measurement includes that, in analytic case, it led to arbitrary precision in measurement of feature; in reasonable test case using the methods proposed, a reasonable and consistent maximum error of around 0.3% the length of a pixel was achieved and in practice using pixels that were 700nm in size feature position was located to within +/- 2 nm. Robust applicability is demonstrated by the measurement of indicator position for a King model 2-32-G-042 rotameter.
机译:在工业控制等适当控制的环境中,可以使用图像配准技术显着突破基于图像的位置测量的非工业约束,并实现像素的0.3%左右的可重复特征测量,或比传统现实世界的性能提高了一个数量级。然后,将这些测量值用作模型优化,不可知模型,平滑激光划痕的校准以及使用视频输入在线跟踪测速仪的输入。使用适当的平滑插值来增加有效样本密度可以减少不确定性并改善估计。使用模板函数的适当负偏移会导致产生比目标函数的任一模板更高的局部曲率的卷积,从而可以改善中心查找。将Akaike信息准则与平滑样条函数一起使用,可以在不知道基础模型的情况下对标量测量执行模型最优平滑,并确定描述该最优平滑中不确定性的函数。然后提供并从中经验推导基本卡尔曼滤波器的参数示例。使用探索性数据分析技术和“公式化”遗传算法工具将样条模型转换为更易于访问的分析形式,从而获得了稳定,正确概括的KF,其性能和简单性超过了其“教科书”实现。测量的验证包括:在分析情况下,它导致特征的测量具有任意精度;在使用提出的方法的合理测试案例中,获得了合理且一致的最大误差,约为像素长度的0.3%,并且在实践中,使用尺寸特征位置为700nm的像素位于+/- 2 nm以内。 King型2-32-G-042转子流量计的指示器位置测量证明了其强大的适用性。

著录项

  • 作者

    Munroe, Michael R.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Mechanical engineering.
  • 学位 M.S.
  • 年度 2012
  • 页码 66 p.
  • 总页数 66
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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