Automatic evaluation of form errors in high-density acquired surfaces - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue International Journal of Production Research Année : 2010

Automatic evaluation of form errors in high-density acquired surfaces

Résumé

In this paper the authors present an original methodology aiming at the automation of the geometric inspection, starting from a high-density acquired surface. The concept of intrinsic nominal reference is herein introduced in order to evaluate geometric errors. Starting from these concepts, a new specification language, which is based on recognizable geometric entities, is defined. This work also proposes some surface differential properties, such as the intrinsic nominal references, from which new categories of form errors can be introduced. Well-defined rules are then necessary for the unambiguous identification of these intrinsic nominal references. These rules are an integral part of the tolerance specification. This new approach requires that a recognition process be performed on the acquired model so as to automatically identify the already-mentioned intrinsic nominal references. The assessable errors refer to recognizable geometric entities and their evaluation leaves the nominal reference specification aside since they can be intrinsically associated with a recognized geometric shape. Tolerance specification is defined based on the error categories which can be automatically evaluated and which are an integral part of the specification language.

Mots clés

Fichier principal
Vignette du fichier
PEER_stage2_10.1080%2F00207541003657370.pdf (1.01 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00588675 , version 1 (26-04-2011)

Identifiants

Citer

Luca Di Angelo, Paolo Di Stefano, Anna Eva Morabito. Automatic evaluation of form errors in high-density acquired surfaces. International Journal of Production Research, 2010, pp.1. ⟨10.1080/00207541003657370⟩. ⟨hal-00588675⟩

Collections

PEER
29 Consultations
113 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More