纺织学报 ›› 2021, Vol. 42 ›› Issue (12): 55-62.doi: 10.13475/j.fzxb.20200904608

• 纺织工程 • 上一篇    下一篇

基于Elasticsearch的纺纱生产数据追溯方法

王波波1,2, 郑小虎2,3(), 申兴旺1, 鲍劲松1, 刘天元1   

  1. 1.东华大学 机械工程学院, 上海 201620
    2.东华大学 人工智能研究院, 上海 201620
    3.上海工业大数据与智能系统工程技术研究中心, 上海 201620
  • 收稿日期:2020-09-18 修回日期:2021-09-24 出版日期:2021-12-15 发布日期:2021-12-29
  • 通讯作者: 郑小虎
  • 作者简介:王波波(1997—),男,硕士。主要研究方向为智能纺纱和设备故障诊断。
  • 基金资助:
    国家重点研发计划项目(2017YFB1304000);国家重点研发计划项目(2019YFB1706300);上海市科技计划项目(20DZ2251400)

Method for data tracing based on Elasticsearch during spinning production

WANG Bobo1,2, ZHENG Xiaohu2,3(), SHEN Xingwang1, BAO Jinsong1, LIU Tianyuan1   

  1. 1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
    2. Institute of Artificial Intelligence, Donghua University, Shanghai 201620, China
    3. Research Center of Shanghai Industrial Big Data and Intelligent System, Shanghai 201620, China
  • Received:2020-09-18 Revised:2021-09-24 Published:2021-12-15 Online:2021-12-29
  • Contact: ZHENG Xiaohu

RichHTML

5

PDF (PC)

50

摘要：

为实现纺纱生产全过程的数字化管理和数据可追溯,提出了一种基于Elasticsearch的纺纱生产数据追溯方法。在考虑纺纱生产全流程的情况下,针对现有的人工标识体系,通过将标识数字化并规范化存储,提高数据可追溯性。同时,通过建立双向追溯方法并设计合理的追溯及融合路径,提高数据追溯性能。与常见的基于MySQL和SQL Server方法的对比实验结果表明:本文方法具有更好的存储稳定性,在追溯速度上分别是MySQL和SQL Server方法的1.6和1.2倍;在数据管理和融合上,采用的数据格式更加灵活,具备可扩展性,该方法在改善纺纱生产的质量溯源方面具有一定的应用价值。

关键词: Elasticsearch, 纺纱生产, 数据追溯, 质量溯源, 数据存储, 数据融合

Abstract:

In order to achieve digital management and data traceability of the entire spinning production process, a method based on Elasticsearch for data tracing during spinning production was proposed. Targeting at the improvement of data traceability, this method took into account the entire process of spinning production and digitalization of the existing manual identification system stored in a standardized manner. At the same time, a two-way tracing method was established and a reasonable tracing fusion path was designed for the improvement of the data tracing performance. The experimental results show that the method offers better storage stability, and the tracing speed when using the proposed method is 1.6 and 1.2 times faster than that of the MySQL and SQL Server implementation method. In terms of data management and fusion, the proposed method is more flexible and scalable. This method has obvious application value in improving the traceability of spinning production.

Key words: Elasticsearch, spinning production, data tracing, quality tracing, data storage, data fusion

中图分类号: 

  • TS111.9

图1

纺纱生产质量溯源问题"

图2

纺纱生产过程时序图"

图3

纺纱生产数据关联性示意图"

图4

基于Elasticsearch的纺纱生产数据追溯框架"

图5

纺纱生产数据前向追溯示意图"

图6

纺纱生产数据追溯路径图"

图7

纺纱生产数据后向追溯示意图"

图8

纺纱生产数据融合示意图"

图9

纺纱生产数据融合路径图"

表1

原始细纱数据内存占用表"

数据个数 MySQL CSV Elasticsearch SQL Server
1 0.016 0.000 4 0.025 6 0.016
10 0.016 0.003 8 0.029 1 0.016
100 0.064 0.038 2 0.136 2 0.048
1 000 0.228 0.386 2 0.575 3 0.336
10 000 2.500 3.900 0 5.100 0 3.100
100 000 26.600 38.900 0 46.500 0 31.400

图10

带标识细纱数据的占用内存"

图11

单过程数据追溯时间随标识添加数量的变化"

图12

多过程数据追溯时间随标识添加数量的变化"

图13

数据融合结果图"

[1] 刘笑莹, 方斌, 朱守艾, 等. 棉/大麻纤维混纺低损耗工艺优化[J]. 纺织学报, 2017, 38(1):35-39.
LIU Xiaoying, FANG Bin, ZHU Shouai, et al. Low-loss optimization of cotton/hemp blending process[J]. Journal of Textile Research, 2017, 38(1):35-39.
[2] 万由顺, 卫江, 桂长明, 等. 全流程智能化纺纱技术创新点及应用效果[J]. 棉纺织技术, 2020, 48(1):28-33.
WAN Youshun, WEI Jiang, GUI Changming, et al. Innovation point and application effect of whole process intelligent spinning technology[J]. Cotton Textile Technology, 2020, 48(1):28-33.
[3] 崔士涛. 利用生产在线信息系统提升纱线质量的实践[J]. 棉纺织技术, 2019, 47(6):67-72.
CUI Shitao. Practice of improving yarn quality by production online information system[J]. Cotton Textile Technology, 2019, 47(6):67-72.
[4] 薛建昌. 棉纺织企业智能化提升方案与应用探讨[J]. 棉纺织技术, 2017, 45(8):1-9.
XUE Jianchang. Improvement scheme and application discussion for the intelligentization in cotton textile enterprise[J]. Cotton Textile Technology, 2017, 45(8):1-9.
[5] AGRAWAL T K, KUMAR V, PAL R, et al. Blockchain-based framework for supply chain traceability: a case example of textile and clothing industry[J]. Computers & Industrial Engineering, 2021. DOI: 10.1016/j.cie.2021.107130.
doi: 10.1016/j.cie.2021.107130
[6] AGRAWAL T K, KOEHL L, CAMPAGNE C. A secured tag for implementation of traceability in textile and clothing supply chain[J]. The International Journal of Advanced Manufacturing Technology, 2018, 99(9):2563-2577.
doi: 10.1007/s00170-018-2638-x
[7] AGRAWAL T K, KOEHL L, CAMPAGNE C. Implementing traceability using particle randomness-based textile printed tags[J]. IOP Conference Series: Materials Science and Engineering, 2017.DOI: 10.1088/1757-899X/254/7/072001.
doi: 10.1088/1757-899X/254/7/072001
[8] FERNANDEZ-CARAMES T M, FRAGA-LAMAS P. A review on human-centered IoT-connected smart labels for the industry 4.0[J]. IEEE Access, 2018, 6:25939-25957.
doi: 10.1109/Access.6287639
[9] JALONEN T, LAAKOM F, GABBOUJ M, et al. Visual product tracking system using siamese neural net-works[J]. IEEE Access, 2021. DOI: 10.1109/ACCESS.2021.3082934.
doi: 10.1109/ACCESS.2021.3082934
[10] 汪松松, 彭来湖, 沈春娅, 等. 针织装备云平台的构建技术[J]. 纺织学报, 2018, 39(10):149-155.
WANG Songsong, PENG Laihu, SHEN Chunya, et al. Construction technology of knitting equipment networking cloud platform[J]. Journal of Textile Research, 2018, 39(10):149-155.
[11] 李传根. Elasticsearch数据存储策略研究[D]. 重庆:重庆邮电大学, 2019:1-32.
LI Chuangen. Research on data storage strategy of Elasticsearch[D]. Chongqing: Chongqing University of Posts and Telecommunications, 2019:1-32.
[12] 胡鑫, 姚宇, 徐英杰. 基于Elasticsearch的TEE病例库检索系统设计与实现[J]. 计算机应用, 2018, 38(S1):91-94.
HU Xin, YAO Yu, XU Yingjie. Design and implementation of electronic medical record system of transesophageal echocardiography based on Elastic-search[J]. Journal of Computer Applications, 2018, 38(S1):91-94.
[13] 李敏波, 许鑫星, 李强, 等. 基于JSON文档结构的工业大数据多维分析方法[J]. 中国机械工程, 2020, 31(14):1700-1707,1716.
LI Minbo, XU Xinxing, LI Qiang, et al. Multi-dimensional analysis method of industrial big data based on JSON document structure[J]. China Mechanical Engineering, 2020, 31(14):1700-1707,1716.
[14] 刘志伟, 邢永旭, 于澔, 等. 企业级海量代码的检索与管理技术[J]. 软件学报, 2019, 30(5):1498-1509.
LIU Zhiwei, XING Yongxu, YU Hao, et al. Retrieval and management technology for industrial-scale massive code[J]. Journal of Software, 2019, 30(5):1498-1509.
[15] 汪小寒, 韩慧慧, 张泽培, 等. 树索引数据差分隐私预算分配方法[J]. 计算机应用, 2018, 38(7):1960-1966.
WANG Xiaohan, HAN Huihui, ZHANG Zepei, et al. Differential privacy budget allocation method for data of tree index[J]. Journal of Computer Applications, 2018, 38(7):1960-1966.
[1] 祁才君;张方强. 纬编织物花型系统中的IC卡技术[J]. 纺织学报, 2001, 22(05): 19-20.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] 曹建达;顾小军;殷联甫. 用BP神经网络预测棉织物的手感[J]. 纺织学报, 2003, 24(06): 35 -36 .
[2] 【作者单位】：中国纺织工程学会秘书处【分类号】：+【DOI】：cnki:ISSN:0-.0.00-0-0【正文快照】：　　香港桑麻基金会设立的“桑麻纺织科技奖” 0 0 年提名推荐工作;在纺织方面院士;专家和有关单位的大力支持下;收到了 个单位 (人 )推荐的 位候选人的. 2003年桑麻纺织科技奖获奖名单[J]. 纺织学报, 2003, 24(06): 107 .
[3] 【分类号】：Z【DOI】：cnki:ISSN:0-.0.00-0-0【正文快照】：　　一;纺　纱模糊控制纺纱张力的研究周光茜等 ( - )………………原棉含杂与除杂效果评价方法的研究于永玲 ( - )……网络长丝纱免浆免捻功能的结构表征方法李栋高等 ( - )……………. 2003年纺织学报第二十四卷总目次[J]. 纺织学报, 2003, 24(06): 109 -620 .
[4] 朱敏;周翔. 准分子激光对聚合物材料的表面改性处理[J]. 纺织学报, 2004, 25(01): 1 -9 .
[5] 张治国;尹红;陈志荣. 纤维前处理用精练助剂研究进展[J]. 纺织学报, 2004, 25(02): 105 -107 .
[6] 秦元春. 纺织工业发展方向初探[J]. 纺织学报, 2004, 25(02): 108 -110 .
[7] 高伟江;魏文斌. 纺织业发展的战略取向——从比较优势到竞争优势[J]. 纺织学报, 2004, 25(02): 111 -113 .
[8] 冯宪. 漫谈未来服装的发展方向[J]. 纺织学报, 2004, 25(02): 119 -120 .
[9] 林红;陈宇岳;任煜;仲志锋;王红卫. 经等离子体处理的蚕丝纤维结构与性能[J]. 纺织学报, 2004, 25(03): 9 -10 .
[10] 潘旭伟;顾新建;韩永生;程耀东. 面向协同的服装供应链快速反应机制研究[J]. 纺织学报, 2006, 27(1): 54 -57 .
京ICP备14006648号　 京公网安备11010502044800号
版权所有 © 2021 《纺织学报》编辑部
地址： 北京市朝阳区延静里中街3号主楼6层《纺织学报》杂志社　邮政编码：100025　
电话：010-65017711,65917740　传真：010-65016539　Email:fangzhixuebao@vip.126.com
本系统由北京玛格泰克科技发展有限公司设计开发