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隧道建设(中英文) ›› 2020, Vol. 40 ›› Issue (3): 371-378.DOI: 10.3973/j.issn.2096-4498.2020.03.009

• 研究与探索 • 上一篇    下一篇

基于VBA 矢量图形识别技术的多源地质信息数据化转换方法

周振建1, 2, 陈 馈1, 2, 高会中1, 2, 褚长海1, 2, 张合沛1, 2, 任颖莹1, 2   

  1. (1. 盾构及掘进技术国家重点实验室, 河南 郑州 450001; 2. 中铁隧道局集团有限公司, 广东 广州 511458)
  • 收稿日期:2019-09-29 出版日期:2020-03-20 发布日期:2020-04-09
  • 作者简介:周振建(1982—),男,四川德阳人,2005 年毕业于辽宁工程技术大学,环境工程专业,本科,工程师,现从事隧道施工技术管理及盾构 掘进技术研究。E-mail: rielchow@ qq. com。
  • 基金资助:
    国家重点研发计划(2018YFB1701404); 郑州市重大科技创新专项(188PCXZX786); 中铁隧道局集团科技创新计划(隧研合2018-40); 中铁隧道局集团科技创新计划(隧研合2018-39)

Datafication Method of Multi-source Geological Information Based on VBA Vector-graphic Recognition Technology

ZHOU Zhenjian1, 2, CHEN Kui1, 2, GAO Huizhong1, 2, CHU Changhai1, 2, ZHANG Hepei1, 2, REN Yingying1,2   

  1. (1. State Key Laboratory of Shield Machine and Boring Technology, Zhengzhou 450001, Henan, China; 2. China Railway Tunnel Group Co., Ltd., Guangzhou 511458, Guangdong, China)
  • Received:2019-09-29 Online:2020-03-20 Published:2020-04-09

摘要: 机器学习算法是全断面隧道掘进机智能化施工技术研究的重要技术手段,其需要大量全面详细的数据化地质信息为基础, 而岩土勘察报告的图、表、文字描述等地质信息却无法直接被机器学习算法辨识。为解决这个问题,提出多源地质信息的数据化转 换方法,即通过编程对CAD、Excel 进行操作,利用VBA 矢量图形识别技术,以给定的参考线为定位基础,自动辨识CAD 地质纵断面 矢量图中隧道穿越的地层,并与岩土勘察报告中的多源地质信息融合,从而得到机器学习算法可辨识的数据化地质信息。与传统 人工法相比,能极大提高效率和数据的准确度,并且可灵活调整数据密度以满足不同需求。通过在全断面隧道掘进机智能辅助掘 进研究中进行应用,取得了良好的效果。

关键词: 全断面隧道掘进机, 地质信息, 数据化转换, 地层识别, VBA

Abstract: The machine learning algorithm is one of the key technical means for the research of intelligent construction technology of full-face tunnel boring machine, which needs a large number of comprehensive and detailed data-based geological information. While, the geological information such as the map, table and text description of geotechnical investigation report cannot be directly identified by machine learning algorithm. Hence, a datafication method of multisource geological information is put forward, which operates CAD and excel by programming, uses VBA vector graphic recognition technology, takes the given reference line as the positioning basis, automatically identifies the strata that the tunnel passes through in the CAD geological profile vector map, and integrates with the multi-source geological information in the geotechnical investigation report, so as to obtain the opportunity data-based geological information that can be identified by machine learning algorithm. Compared with the traditional manual method, the method mentionedabove can greatly improve the efficiency and accuracy of the data, and can flexibly adjust the data density to meet different needs. The method has been applied in the research of intelligent auxiliary driving of full-face tunnel boring machine, and good effects have been achieved.

Key words: full-face tunnel boring machine, geological information, datafication, stratum recognition, VBA

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