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research-article

Assessment of the robustness of a fixtureless inspection method for non-rigid parts based on a verification and validation approach

[+] Author and Article Information
Sasan Sattarpanah Karganroudi

Équipe de Recherche en Intégration Cao-CAlcul (ÉRICCA), Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
Sasan.Sattarpanah.Karganroudi@uqtr.ca

Jean-Christophe Cuilliere

Équipe de Recherche en Intégration Cao-CAlcul (ÉRICCA), Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
cuillier@uqtr.ca

Vincent Francois

Équipe de Recherche en Intégration Cao-CAlcul (ÉRICCA), Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
vincent.francois@uqtr.ca

Antoine S. Tahan

Laboratoire d'ingénierie des produits, procédés et systèmes (LIPPS), École de Technologie Supérieure, Montréal, Québec, Canada
antoine.tahan@etsmtl.ca

1Corresponding author.

ASME doi:10.1115/1.4038917 History: Received October 07, 2016; Revised December 22, 2017

Abstract

The increasing practical use of Computer-Aided Inspection (CAI) methods requires assessment of their robustness in different contexts. This can be done by quantitatively comparing estimated CAI results with actual measurements. The objective is comparing the magnitude and dimensions of defects as estimated by CAI with those of the actual defects. This assessment is referred to as setting up a validation metric. In this work, a new validation metric is proposed in the case of a fixtureless inspection method for non-rigid parts. It is based on using a nonparametric statistical hypothesis test, namely the Kolmogorov-Smirnov (K-S) test. This metric is applied to an automatic fixtureless CAI method for non-rigid parts developed by our team. This fixtureless CAI method is based on calculating and filtering sample points that are used in a finite element non-rigid registration (FENR). Robustness of our CAI method is validated for the assessment of maximum amplitude, area and distance distribution of defects. Typical parts from the aerospace industry are used for this validation and various levels of synthetic measurement noise are added to the scanned point cloud of these parts to assess the effect of noise on inspection results.

Copyright (c) 2017 by ASME
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