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Structured light system design for nondestructive evaluation imaging.

机译:用于无损评估成像的结构化照明系统设计。

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摘要

In this thesis project, we have developed and implemented a prototype for evaluation of natural gas plastic Pipes. We implemented this on raspberry pi for experimental analysis using real time processing. The whole platform consists of 3 inch diameter plastic module built using 3d printer, which holds structured light laser source, a fish eye camera and embedded board for processing and recognizing defects of the inner pipeline structure that is not easily accessible for human inspectors. The embedded machine acquires the data from connected camera via serial bus and follows the 3d rendering algorithm. The algorithm is designed to process the data in real time and render all 2d frames into 3D pipe with exactly same features of pipe. The prototype was developed on a level-by-level approach. Firstly, we implemented using an optical camera with 90-degree field of view that can only cover a part of structured light. Secondly, we use a fisheye camera with 180-degree field of view, which gives desired results of complete ring, which is used as the input of developed rendering algorithm. According to above-mentioned method the motion of camera within pipe is assumed to be constant (10 frames per cm). Finally, the location of cracks within pipes can be detected and the size of cracks can also be recognized using number of frames. The profile of cracks can easily be seen on rendered 3d structure. The raspberry pi is limiting the use of prototype in long length pipes because as the length increase it leads to huge volume of data and can't be handled using limited computational power of pi. The possibility of the future work would include the use of graphic processing unit for faster processing and rendering.
机译:在本论文项目中,我们开发并实现了用于评估天然气塑料管道的原型。我们在树莓派上实现了此功能,以便使用实时处理进行实验分析。整个平台包括使用3d打印机构建的直径为3英寸的塑料模块,该模块容纳结构化的激光光源,鱼眼摄像头和嵌入式板,用于处理和识别内部管道结构的缺陷,这些缺陷是人类检查人员难以接近的。嵌入式机器通过串行总线从连接的摄像机获取数据,并遵循3d渲染算法。该算法旨在实时处理数据,并将所有2d帧渲染到具有与管道完全相同的特征的3D管道中。原型是逐级开发的。首先,我们使用具有90度视野的光学相机来实现,该相机只能覆盖部分结构光。其次,我们使用具有180度视场的鱼眼镜头相机,它可以提供完整的环形效果,并用作开发的渲染算法的输入。根据上述方法,假定摄像机在管道内的运动是恒定的(每厘米10帧)。最终,可以检测出管道内裂缝的位置,并且还可以使用帧数识别裂缝的大小。在渲染的3d结构上可以轻松看到裂缝的轮廓。覆盆子pi限制了原型在长管中的使用,因为随着长度的增加,它会导致大量数据,并且无法使用pi的有限计算能力来处理。未来工作的可能性将包括使用图形处理单元进行更快的处理和渲染。

著录项

  • 作者

    Buggaveeti, Praneeth.;

  • 作者单位

    University of Colorado at Denver.;

  • 授予单位 University of Colorado at Denver.;
  • 学科 Electrical engineering.
  • 学位 M.S.
  • 年度 2016
  • 页码 81 p.
  • 总页数 81
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 石油、天然气工业;
  • 关键词

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