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APPLICATION OF INFRARED PHOTOGRAPHY AND IMAGE PROCESSING IN NATM TUNNEL

机译:红外照相和图像处理在NATM隧道中的应用

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摘要

There is lots of dust in the constructing rock tunnel with New Austrian Tunneling Method. Since the length of visible light wave is shorter than dust, and the light is always not sufficient in the tunnel, it's hard to get clear pictures with classical photography technique. Using the infrared photography technology, it is possible to get vivid picture through dust and fog for the length of infrared wave is close to dust. This paper specifies the process of shooting tunnel face with infrared technology in the constructing rock tunnel. Based on sufficient experience of taking pictures of tunnel face with this method, regulation has been advanced which describes how to get clear pictures in the complex circumstance in constructing rock tunnel with the special equipments. Based on former researches of identifying the digital photographs of tunnel face with joints and cracks, this paper has attempted several ways of image processing and intelligent recognition on the tunnel face photographs. After the comparing and analyzing of the results, regulations of image processing and intelligent recognition which are fit for this kind of photographs was advanced. Infrared photography which is described in this paper is a useful innovation for getting clear tunnel face photograph in constructing rock tunnel with NATM. The image processing implements semi-automatic geological sketching. The intelligent recognition of tunnel face images provides some critical parameters for rock masses classification, and makes 3-D numeral reconstruction of the tunnel more precise and convenient.
机译:用新奥地利隧道法施工的岩石隧道中灰尘很多。由于可见光波的长度比尘埃短,并且隧道中的光线始终不足,因此采用传统摄影技术很难获得清晰的图像。使用红外线摄影技术,由于红外线的长度接近灰尘,因此可以通过灰尘和雾获得逼真的图像。本文详细介绍了在岩洞施工中采用红外技术对隧道面进行射孔的过程。在此基础上,利用丰富的隧道面照相经验,提出了在特殊环境下用专用设备建造岩洞时如何获取清晰图像的规定。在对识别具有缝隙和裂缝的隧道工作面数码照片的先前研究的基础上,本文尝试了多种方法对隧道工作面照片进行图像处理和智能识别。在对结果进行比较分析后,提出了适合此类照片的图像处理和智能识别的规定。本文描述的红外照相技术是有用的创新,它可以在使用NATM构造岩石隧道时获得清晰的隧道面照片。图像处理实现了半自动地质素描。隧道面图像的智能识别为岩体分类提供了一些关键参数,并使隧道的3D数字重建更加精确和方便。

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  • 来源
  • 会议地点 Nanjing(CN)
  • 作者

    TAN Jingrong; rnWANG Yifen;

  • 作者单位

    Chunlin Zhou@Department of Geotechnical Engineering, Tongji University, 1239 Siping Road,Shanghai 210030, China--Hehua Zhu@Department of Geotechnical Engineering, Tongji University, 1239 Siping Road,Shanghai 210030, China--Xiaojun Li@Department of Geotechnical Engineering, Tongji University, 1239 Siping Road,Shanghai 210030, China--;

  • 会议组织
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  • 正文语种
  • 中图分类 灾害地质学;
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