Toward Template-Based Tolerancing from a Bayesian Viewpoint

Noble, J. Alison; Mundy, Joe L.

doi:10.1109/CVPR.1993.340982

Toward Template-Based Tolerancing from a Bayesian Viewpoint

J. Alison Noble, Joe L. Mundy

CVPR 1993 pp. 246-252

doi:10.1109/CVPR.1993.340982 /cvpr/1993/noble1993cvpr-template/

Abstract

A novel approach to part tolerancing with measurement error based on Bayesian methods is presented. Parts are represented by parameterised constraint templates. A priori knowledge about expected part geometry is introduced through a prior distribution and template parameter distributions (rather than just nominal parameter values) estimated from data sets using Gibbs sampling. The case of a toleranced dimension and linear constraints is analyzed. An extension to nonlinear constraints is briefly described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

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Cite

Text

Noble and Mundy. "Toward Template-Based Tolerancing from a Bayesian Viewpoint." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.340982

Markdown

[Noble and Mundy. "Toward Template-Based Tolerancing from a Bayesian Viewpoint." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/noble1993cvpr-template/) doi:10.1109/CVPR.1993.340982

BibTeX

@inproceedings{noble1993cvpr-template,
  title     = {{Toward Template-Based Tolerancing from a Bayesian Viewpoint}},
  author    = {Noble, J. Alison and Mundy, Joe L.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {246-252},
  doi       = {10.1109/CVPR.1993.340982},
  url       = {https://mlanthology.org/cvpr/1993/noble1993cvpr-template/}
}