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Research Papers

Feature-Based Solid Model Reconstruction

[+] Author and Article Information
Jun Wang

College of Mechanical and
Electrical Engineering,
Nanjing University of Aeronautics
and Astronautics,
Nanjing 210016, China
e-mail: davis.wjun@gmail.com

Dongxiao Gu

School of Management,
Hefei University of Technology,
Hefei 230009, China
e-mail: mikehfut@gmail.com

Zhanheng Gao

Institute of Mathematics,
Jinlin University,
Changchun 130012,China
e-mail: gaozhanheng@gmail.com

Zeyun Yu

Department of Computer Science,
University of Wisconsin-Milwaukee,
Milwaukee, WI 53211
e-mail: yuz@uwm.edu

Changbai Tan

e-mail: tcbnuaa@nuaa.edu.cn

Laishui Zhou

e-mail: zlsme@nuaa.edu.cn
College of Mechanical and
Electrical Engineering,
Nanjing University of Aeronautics
and Astronautics,
Nanjing 210016, China

Contributed by the Computers and Information Division of ASME for publication in the Journal of Computing and Information Science in Engineering. Manuscript received August 9, 2011; final manuscript received November 2, 2012; published online January 10, 2013. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 13(1), 011004 (Jan 10, 2013) (13 pages) Paper No: JCISE-11-1399; doi: 10.1115/1.4023129 History: Received August 09, 2011; Revised November 02, 2012

In this paper, we propose an effective solution to reconstruct solid models of existing objects. Specifically, we convert the model reconstruction problem into the issue of feature parameter extraction, and thereby design diverse methods to extract the parameters of basic design features from input surface meshes. After extracting the feature parameters, the corresponding features are constructed. By performing modeling operations on those features, the final solid model is constructed, and meanwhile the complete history of the model building operations is recorded. By introducing the concepts of “feature,” “constraint,” and “modeling history” into the reconstruction process, the design intent is captured and hence represented in the reconstructed model. As a result, the model is geometrically accurate and topologically consistent, and moreover it is flexibly editable, which makes it convenient to carry out model redesign and modification for the innovation applications. A variety of experimental results demonstrate the effectiveness and robustness of this solution.

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Figures

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Fig. 1

Reconstruction of a 2D contour from sectional points in an industrial part. (a) The point set of the part; (b) the sectional points from the part; (c) the curvature distribution graph; (d) the sectional point segmentation result, where each segment consists of the points bounded by two adjacent “cross points”; (e) the curves individually fitted from segments; (f) the potential constraints; and (g) the final contour fitted with constraints. Again, the reconstruction result is favorable.

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Fig. 2

Reconstruction of a 2D contour from sectional points in a blade part. (a) The point set of the blade; (b) the section points from the blade; (c) the fitted curve segments; (d) the potential constraints among curves; and (e) the final contour. Note that the contour is reconstructed with a good result.

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Fig. 3

Reconstruction of an extrude feature. (a) The point set on the side surfaces of the part; (b) the normal vectors of the point set; (c) the extrusion direction; (d) the sectional points; (e) the reconstructed 2D contour; and (f) the reconstructed feature.

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Fig. 4

Extraction of the revolution axis of the revolve feature

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Fig. 5

Extraction of the revolution contour of the revolve feature

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Fig. 6

Reconstruction of the revolve feature in a mechanical part. (a) The triangular mesh of the part; (b) the normal vectors of the point set; (c) the revolution axis; (d) the sectional points; (e) the reconstructed revolution contour; and (f) the reconstructed feature.

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Fig. 7

Reconstruction of a sweep feature. (a) The triangular mesh of the feature; (b) the reconstructed sweep path and profile; (c) the reconstructed sweep feature; (d) the reconstruction error graph. The diameter of the bounding sphere of the feature is 2.960 and the average edge length of the input mesh is 0.024, while the maximum error is 0.010. Again, the reconstruction result is favorable.

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Fig. 8

2D illustration of iterative construction of an optimal section plane of a point on the loft surface. (a)–(c) The section plane anchored at pi from πi0 to πi⋆ and converges. During iteration, the normal vector of the next section plane makes the same angle with those normal vectors at the boundary, corresponding to the current section plane.

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Fig. 9

Reconstruction of a screwdriver model (loft feature). (a) The triangular mesh of the model; (b) the loft profile sections; (c) the reconstructed screwdriver model; and (d) the reconstruction error graph. The diameter of the bounding sphere of the feature is 0.098 and the average edge length of the input mesh is 0.0017, while the maximum error is 0.00068. Notice that the error is comparatively small.

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Fig. 10

The illustration of the generation of blend feature

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Fig. 11

The illustration of determining the section plane of blend feature

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Fig. 12

The distribution of radius for three cases

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Fig. 13

Reconstruction of mechanical parts with blend features. (a) The triangular mesh of a mechanical part containing the blend feature with the linear variable radius profile; (b) the series of profile curves (circles); (c) the reconstructed feature; (d) the feature in the original model; (e)–(h) The reconstruction of the blend feature with the nonlinear variable radius profile; (i), (j) The radius distribution of the blend features in (a) and (f). From (i), we can see that the fitting error is quite small, indicating that the radius varies linearly, while the radius distribution in (j) shows that the radius varies nonlinearly.

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Fig. 14

Model reconstruction of a mechanical part. (a) The original triangular mesh of the part; (b) a reconstructed 2D contour and the corresponding extrude feature; (c) another reconstructed 2D contour and the corresponding extrude feature; (d) all reconstructed features aligned in a view; (e) back view of all reconstructed features; (f) the final reconstructed model; (g) the reconstruction error graph, where the average edge length of the input mesh is 4.889, while the maximum error is 1.853. (h) A modified 2D contour of (c) by changing the radii of arcs; (i) the new feature from (h); (j) the new model.

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Fig. 15

Model reconstruction of another mechanical part. (a) The original triangular mesh of the part; (b) a reconstructed 2D contour and the corresponding extrude feature; (c) a series of sampled profile sections and the reconstructed loft feature; (d) a reconstructed 2D contour and the corresponding revolve feature; (e) the final reconstructed model; (f) the reconstruction error graph, where the average edge length of the input mesh is 0.099, while the maximum error is 0.011. (g) A redesigned model from (e).

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Fig. 16

Model reconstruction of a cup. (a) The original triangular mesh of the teapot; (b) the reconstructed sweep profile and path; (c) the reconstructed contour and axis of a revolve feature; (d) the final reconstructed model; (e) the reconstruction error graph, where the average edge length of the input mesh is 0.877, while the maximum error is 0.324. (f) The sweep profile modified by changing the radius, and the sweep path modified by adjusting control points from (b); (g) the modified revolution contour from (d); (h) the new model.

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Fig. 17

Solid models reconstructed from our method

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