With the material processing freedoms of additive manufacturing (AM), the ability to characterize and control material microstructures is essential if part designers are to properly design parts. To integrate material information into Computer-aided design (CAD) systems, geometric features of material microstructure must be recognized and represented, which is the focus of this paper. Linear microstructure features, such as fibers or grain boundaries, can be found computationally from microstructure images using surfacelet based methods, which include the Radon or Radon-like transform followed by a wavelet transform. By finding peaks in the transform results, linear features can be recognized and characterized by length, orientation, and position. The challenge is that often a feature will be imprecisely represented in the transformed parameter space. In this paper, we demonstrate surfacelet-based methods to recognize microstructure features in parts fabricated by AM. We will provide an explicit computational method to recognize and to quantify linear geometric features from an image.

References

References
1.
Qian
,
X.
, and
Dutta
,
D.
,
2003
, “
Physics-Based Modeling for Heterogeneous Objects
,”
ASME J. Mech. Des.
,
125
(
3
), pp.
416
427
.10.1115/1.1582877
2.
Rosen
,
D. W.
,
Jeong
,
N.
, and
Wang
,
Y.
,
2013
, “
A Method for Reverse Engineering of Material Microstructure for Heterogeneous CAD
,”
Comput.Aided Des.
,
45
(
7
), pp.
1068
1078
.10.1016/j.cad.2013.01.004
3.
Edwards
,
P.
,
O'Conner
,
A.
, and
Ramulu
,
M.
,
2013
, “
Electron Beam Additive Manufacturing of Titanium Components: Properties and Performance
,”
ASME J. Manuf. Sci. Eng.
,
135
(
6
), p.
061016
.10.1115/1.4025773
4.
Mason
,
T. A.
, and
Adams
,
B. L.
,
1999
, “
Use of Microstructural Statistics in Predicting Polycrystalline Material Properties
,”
Metall. Mater. Trans. A
,
30A
(
4
), pp.
969
979
.10.1007/s11661-999-0150-5
5.
Saheli
,
G.
,
Garmestani
,
H.
, and
Adams
,
B. L.
,
2004
, “
Microstructure Design of a Two Phase Composite Using Two-Point Correlation Functions
,”
J. Comput.Aided Mater. Des.
,
11
(
2–3
), pp.
103
115
.10.1007/s10820-005-3164-3
6.
Kalidindi
,
S. R.
, and
Houskamp
,
J. R.
,
2007
, “
Application of the Spectral Methods of Microstructure Design to Continuous Fiber-Reinforced Composites
,”
J. Compos. Mater.
,
41
(
8
), pp.
909
930
.10.1177/0021998306067256
7.
Searles
,
T.
,
Tiley
,
J.
,
Tanner
,
A.
,
Williams
,
R.
,
Rollins
,
B.
,
Lee
,
E.
,
Kar
,
S.
,
Banerjee
,
R.
, and
Fraser
,
H. L.
,
2005
, “
Rapid Characterization of Titanium Microstructural Features for Specific Modeling of Mechanical Properties
,”
Meas. Sci. Technol.
,
16
(
1
), pp.
60
69
.10.1088/0957-0233/16/1/009
8.
Brahme
,
A.
,
Alvi
,
M. H.
,
Saylor
,
D.
,
Fridy
,
J.
, and
Rollett
,
A. D.
,
2006
, “
3D Reconstruction of Microstructure in a Commercially Purity Aluminum
,”
Scr. Mater.
,
55
(
1
), pp.
75
80
.10.1016/j.scriptamat.2006.02.017
9.
Jeong
,
N.
,
Rosen
,
D. W.
, and
Wang
,
Y.
,
2013
, “
A Comparison of Surfacelet-Based Methods for Recognizing Linear Geometric Features in Material Microstructure
,”
ASME
Paper No. DETC2013-13370.10.1115/DETC2013-13370
10.
Leavers
,
V.
, and
Boyce
,
J.
,
1987
, “
The Radon Transform and its Application to Shape Parametrization in Machine Vision
,”
Image Vision Comput.
,
5
(
2
), pp.
161
166
.10.1016/0262-8856(87)90044-8
11.
Leavers
,
V.
,
1992
, “
Use of the Radon transform as a Method of Extracting Information About Shape in two Dimensions
,”
Image Vision Comput.
,
10
(
2
), pp.
99
107
.10.1016/0262-8856(92)90004-M
12.
Niezgoda
,
S. R.
, and
Kalidindi
,
S. R.
,
2009
, “
Applications of the Phase-Coded Generalized Hough Transform to Feature Detection, Analysis, and Segmentation of Digital Microstructures
,”
Comput., Mater. Contin.
,
14
(
2
), pp.
79
98
.10.3970/cmc.2009.014.079
13.
Wang
,
Y.
, and
Rosen
,
D. W.
,
2010
, “
Multiscale Heterogeneous Modeling With Surfacelets
,”
Comput. Aided Des. Appl.
,
7
(
5
), pp.
759
776
.10.3722/cadaps.2010.759-776
14.
Kak
,
A. C.
, and
Slaney
,
M.
,
2001
,
Principles of Computerized Tomographic Imaging
, Vol.
120
,
Siam
,
Philadelphia, PA
.10.1137/1.9780898719277
15.
Do
,
M. N.
, and
Vetterli
,
M.
,
2003
, “
The Finite Ridgelet Transform for Image Representation
,”
IEEE Trans. Image Process.
,
12
(
1
), pp.
16
28
.10.1109/TIP.2002.806252
16.
Lanzavecchia
,
S.
,
Bellon
,
P. L.
, and
Radermacher
,
M.
,
1999
, “
Fast and Accurate Three-Dimensional Reconstruction From Projections With Random Orientations Via Radon Transforms
,”
J. Struct. Biol.
,
128
(
2
), pp.
152
164
.10.1006/jsbi.1999.4185
17.
Jiang
,
X.
,
Zeng
,
W.
,
Scott
,
P.
,
Ma
,
J.
, and
Blunt
,
L.
,
2008
, “
Linear Feature Extraction Based on Complex Ridgelet Transform
,”
Wear
,
264
(
5
), pp.
428
433
.10.1016/j.wear.2006.08.040
18.
Daubechies
,
I.
,
Runborg
,
O.
, and
Sweldens
,
W.
,
2004
, “
Normal Multiresolution Approximation of Curves
,”
Constr. Approximation
,
20
(
3
), pp.
399
463
.10.1007/s00365-003-0543-4
19.
Shenoy
,
M.
,
Tjiptowidjojo
,
Y.
, and
McDowell
,
D.
,
2008
, “
Microstructure-Sensitive Modeling of Polycrystalline IN 100
,”
Int. J. Plast.
,
24
(
10
), pp.
1694
1730
.10.1016/j.ijplas.2008.01.001
20.
Wang
,
F.
,
Mei
,
J.
, and
Wu
,
X.
,
2006
, “
Microstructure Study of Direct Laser Fabricated Ti Alloys Using Powder and Wire
,”
Appl. Surf. Sci.
,
253
(
3
), pp.
1424
1430
.10.1016/j.apsusc.2006.02.028
21.
Murr
,
L. E.
,
Gaytan
,
S. M.
,
Ramirez
,
D. A.
,
Martinez
,
E.
,
Martinez
,
J. L.
,
Hernandez
,
D. H.
,
Machado
,
B. I.
,
Medina
,
F.
, and
Wicker
,
R. B.
,
2010
, “
Microstructure Architecture Development in Metals and Alloys by Additive Manufacturing Using Electron Beam Melting
,”
Solid Freeform Fabrication Symposium
,
Austin, TX,
Aug. 9–11, pp.
308
323
.
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