Research Papers

Nonrigid Registration for Form Defect Identification of Thin Parts

[+] Author and Article Information
F. Thiébaut

ENS Cachan University Paris-Sud,
Université Paris-Saclay,
Cachan 94235, France
e-mail: francois.thiebaut@ens-cachan.fr

S. Bendjebla

ENS Cachan University Paris-Sud,
Université Paris-Saclay,
Cachan 94235, France
e-mail: soumiya.bendjebla@ens-cachan.fr

Y. Quinsat

ENS Cachan University Paris-Sud,
Université Paris-Saclay,
Cachan 94235, France
e-mail: yann.quinsat@ens-cachan.fr

C. Lartigue

ENS Cachan University Paris-Sud,
Université Paris-Saclay,
Cachan 94235, France
e-mail: claire.lartigue@ens-cachan.fr

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received June 20, 2017; final manuscript received February 21, 2018; published online April 26, 2018. Assoc. Editor: John Michopoulos.

J. Comput. Inf. Sci. Eng 18(2), 021012 (Apr 26, 2018) (7 pages) Paper No: JCISE-17-1123; doi: 10.1115/1.4039640 History: Received June 20, 2017; Revised February 21, 2018

The paper discusses thin part inspection using three-dimensional (3D) non rigid registration. The main objective is to match measurement point data to its nominal representation, so as to identify form defects. Since form defects have the same size order as the thickness of the part, establishing such matching is a challenging task. The originality of the method developed in this paper is using a deformable iterative closet point algorithm (ICP), and integrating modal approach to express form defects. The method described improves the matching through iteration of the ICP and establishes a definition of the error. The results of the application show that the present method is efficient.

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Grahic Jump Location
Fig. 1

A thin part, its CAD model and the measured points

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Fig. 2

Examples of bad matching

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Fig. 3

Overview of the algorithm

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Fig. 4

Simple test part—CAD model and measured data

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Fig. 5

Correspondence between point clouds

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Fig. 6

Representation of eigenmodes for a 2D beam

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Fig. 7

Alignement of the two point sets

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Fig. 8

Initial deviations after a coarse rigid registration

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Fig. 9

Final modal coefficients

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Fig. 10

Most influential natural modes (7, 10, 19)

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Fig. 11

Residual form deviations before(left) and after (right) bad pairs rejection

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Fig. 12

Histogram of the deviations ξi

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Fig. 13

Cartography of the form deviations



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