深度学习背景下的岭南传统手工编织技艺系统整合研究

Jiali Li, Shuai He
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引用次数: 0

摘要

摘要本文首先在岭南地区传统手工编织技术的基础上,运用现代数字技术对其进行系统整合,构建立体编织技术。其次,根据三维机织物在横截面内的运动轨迹,通过两步和四步织造方法研究了三维机织物的结构特性。最后,对竹编材料的基本性能进行分析,以便利用结构模拟分析软件SIM-SOLID对获得的参数化岭南地区竹编工艺产品形态模型样品进行受力模拟分析。结果表明:在竹编工艺产品结构受力研究中,取加载周期各阶段的第一迟滞回线计算等效粘性阻尼系数,其最大变形量为0.428 mm,比无固定节点模型小0.003 mm,表明采用三维编织技术对岭南地区织造工艺性能有明显优化。本文为岭南地区传统手工编织工艺的数字化整合和编织材料结构性能的提升提供了理论参考。
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A Systematic Integration Study of Traditional Hand-Weaving Techniques in Lingnan Region in the Context of Deep Learning
Abstract In this paper, firstly, on the basis of the traditional hand weaving technique in Lingnan area, modern digital technology is used to integrate it systematically, so as to construct the three-dimensional weaving technique. Secondly, the structural properties of the three-dimensional woven fabrics are investigated through the two-step and four-step weaving methods in terms of the movement trajectories of the three-dimensional woven fabrics within the cross-section. Finally, the basic properties of bamboo weaving materials were analyzed in order to facilitate the force simulation analysis of the obtained morphological model samples of parametric Lingnan region bamboo weaving craft products using the structural simulation analysis software SIM-SOLID. The results show that in the structural force study of bamboo weaving craft products, the equivalent viscous damping coefficient is calculated by taking the first hysteresis loop of each stage of the loading cycle, and its maximum deformation is 0.428 mm, which is 0.003 mm smaller than that of the model with unfixed joints, which indicates that the performance of the Lingnan region weaving technique is optimized obviously by adopting the three-dimensional weaving technique. This paper provides theoretical references for the digital integration of traditional hand-woven techniques and the enhancement of structural properties of woven materials in the Lingnan region.
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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