Domestic advance progress of intelligent cotton textile based on CiteSpace graph

doi:10.19398/j.att.202206055

Abstract

Abstract: In recent year, with the progress of the Internet of Things, artificial intelligence, and big data, etc. the intelligent research of textile industry has developed rapidly. Bibliometrics and the knowledge graph method were used as the research method, and CiteSpace scientific literature visualization analysis software was used to visually analyze the publication volume, research units, authors, and keywords of each year over the previous 20 years in order to clearly understand the research status and trend of cotton spinning enterprise intelligence in China. The findings demonstrate that China's cotton textile industry has undergone a scale of intelligent research in recent years, and literary study in this area has generally shown an increasing trend. However, there is a lack of network density among research teams and employees, poor communication, insufficient cooperation, and imperfect exchange and cooperation mechanisms. Digitalization, intelligence, and energy conservation have emerged as the top research trends for cotton textile intelligent firms, and intelligent research has grown in popularity according to the keyword map. Finally, A more developed intelligent system team should then be formed by universities, research institutes, etc. after improving collaboration and information exchanges with cotton spinning businesses. In order to achieve low equipment manufacturing costs, large data flows, and intelligent self-sustainability, it is also important to strengthen interdisciplinary integration and in-depth integration with businesses. This will help to promote the application of intelligent and sustainable development in China's textile industry.

Key words: bibliometrics, CiteSpace, cotton spinningmachinery, intelligent, tex-superpower

摘要： 随着物联网、人工智能和大数据等技术的进步,近年来纺织行业智能化研究迅速开展。为了解国内棉纺智能化研究发展现状和趋势,本文基于中国知网全文数据库,采用可视化图谱对比分析法,利用CiteSpace科学文献可视化分析软件,对最近20年中各年度文献的发表量、研究单位与作者和关键词展开可视化分析。结果表明:目前中国棉纺智能化研究已初具规模,相关研究文献在数量上整体呈现上升趋势,但是研究单位和作者网络密度较小,交流较少及合作不够紧密,同时未能形成良好的合作交流机制;通过对关键词图谱分析得出,智能化研究已属研究热点,数字化、智能化和节能成为棉纺智能化企业的研究趋势。最后,建议纺织高校、研究机构等不仅要加强与棉纺企业的合作交流,形成较为成熟的智能化体系团队,还要加快学科交叉融合以及与企业相互之间的深度融合,实现设备制造成本低、数据流通量大及智能化的自立自强,推动中国纺织行业智能化的可持续发展与应用。

关键词: 文献计量, CiteSpace, 棉纺机械, 智能化, 纺织强国

CLC Number:

TS102.2⁺11

CAO Jiqiang, WANG Yong, TANG Xinjun, CHEN Chao. Domestic advance progress of intelligent cotton textile based on CiteSpace graph[J]. Advanced Textile Technology, 2022, 30(6): 1-7.

曹吉强, 王勇, 唐新军, 陈超. 基于CiteSpace的国内棉纺智能化研究图谱分析[J]. 现代纺织技术, 2022, 30(6): 1-7.

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