现代纺织技术 ›› 2022, Vol. 30 ›› Issue (6): 1-7.DOI: 10.19398/j.att.202206055

• 特约专栏:纺织文献计量分析 •    下一篇

基于CiteSpace的国内棉纺智能化研究图谱分析

曹吉强1,4, 王勇2, 唐新军3, 陈超4,5   

  1. 1.新疆大学纺织与服装学院,乌鲁木齐 830017;
    2.安徽工程大学纺织服装学院,安徽芜湖 241000;
    3.新疆工程学院机电工程学院,乌鲁木齐 830023;
    4.东华大学纺织学院,上海 201620;
    5.济宁如意新材料技术有限公司,山东济宁 272000
  • 收稿日期:2022-06-30 出版日期:2022-11-10 网络出版日期:2022-11-16
  • 作者简介:曹吉强(1988—),男,江苏邳州人,讲师,主要从事纺织材料、纱线结构与性能及新型纺纱技术和纺织品设计方面的研究。
  • 基金资助:
    国家自然科学基金项目(51963020);国家级大学生创新训练项目(202210755022);新疆维吾尔自治区自然科学基金项目(2020D01C079)

Domestic advance progress of intelligent cotton textile based on CiteSpace graph

CAO Jiqiang1,4, WANG Yong2, TANG Xinjun3, CHEN Chao4,5   

  1. 1. College of Textile and Fashion, Xinjiang University, Urumqi 830017, China;
    2. School of Textile and Garment, Anhui Polytechnic University, Wuhu 241000, China;
    3. College of Mechanical and Electrical Engineering, Xinjiang Institute of Engineering, Urumqi 830023, China;
    4. College of Textiles, Donghua university, Shanghai 201620, China;
    5. Jining Ruyi New Material Technology Co., Ltd. , Jining 272000, China
  • Received:2022-06-30 Published:2022-11-10 Online:2022-11-16

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

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

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