Direction Estimation and Visualization of Yarns from CT Volumes of SiC Fabric
Author(s) -
Yukie Nagai,
Yutaka Ohtake,
Hiromasa Suzuki,
Hiroyuki Hishida,
Koichi Inagaki,
Takeshi Nakamura
Publication year - 2016
Publication title -
international journal of automation technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.513
H-Index - 18
eISSN - 1883-8022
pISSN - 1881-7629
DOI - 10.20965/ijat.2016.p0179
Subject(s) - materials science , thermostability , ceramic , stiffness , composite material , visualization , volume (thermodynamics) , ceramic matrix composite , computer science , artificial intelligence , biochemistry , chemistry , physics , quantum mechanics , enzyme
Ceramic matrix composite (CMC) is a material with high thermostability. Since it is lower in weight than metals realizing the same thermostability, it has been attracting increasing attention in many fields. It has an inner fabric structure made of ceramics (SiC), and the yarns of the fabric give this material rather high stiffness in the directions the yarns run. To guarantee the stiffness of the material, it is necessary to inspect the yarns. X-ray CT scanning, a non-destructive inspection technique, is one of the best ways to do this. However, the quality of a CT volume of SiC fabric tends to be very low, and the resolution is generally also low because of the restriction on the time given for the inspection and the relatively large size of CMC parts. This paper presents an algorithm for computing the directions of the yarns in an SiC fabric from a low quality CT volume, and it proposes a way to visualize the computed directions for a better recognition of the directions. It also presents some experimental results that show the effects of the proposed algorithms.
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