Paper Info
Title
Prediction Of Skewness For Plain-Knitted Fabric Based On The Modeling Of Knitted Structure
Abstract
A method for modeling skewness of plain-knitted fabric is proposed. It is important to model structures consisting of deformable linear objects such as wires, clothes, and so on because properties of these linear objects affect the behavior of the structure, for example, skewness. It is a phenomenon that plain-knitted fabric is deformed with inclination. It degrades the quality of plain-knitted fabric. From a mechanical point of view, skewness can be interpreted as follows: the torsional deformation of a twisted linear object (a yarn) is converted into the bending deformation because the structure consisting of them (knitted fabric) becomes stable by minimizing its energy. Therefore, first, we model a twisted yarn to uniformly deal with its bending and torsional deformation. Then, a knitted stitch is modeled based on the differential geometry without arbitrary representation. Furthermore, a skew stitch is modeled by extending the model of a knitted stitch. Finally, the validity of our proposed method is shown by comparing the simulated skew shape and the actual one.
Year
Venue
Field
2017
2017 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII)
Computer vision,Yarn,Skewness,Torsion (mechanics),Bending,Artificial intelligence,Skew,Differential geometry,Engineering,Deformation (mechanics),Structural engineering
DocType
ISSN
Citations 
Conference
2474-2317
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yosuke Inui100.34
Hidefumi Wakamatsu215519.11
Eiji Morinaga3104.06
Eiji Arai48417.87