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Development of the georadar observation model for underground infrastructure detection

机译:地下基础设施探测的雷达雷达观测模型的开发

摘要

The necessity for the implementation of non-destructive methods for recording has arisen from our long term practical experience of extremely wide range of solutions regarding establishment, management and maintenance of the Consolidated Cadastre of Public Infrastructure of the Republic of Slovenia, as well as from our daily work in the field of recording infrastructure consisting of public utilities, energy infrastructure and communication facilities. Similar trends may now also be observed elsewhere in the world. In this thesis, ground-penetrating radar (GPR) observation for monitoring buried utilities based on controlled testing pool environment has been designed and proposed as a three phase process. In the first phase, the kinematic method for positioning GPR is introduced and geophysical and geodetic sets of observation are connected. In the second phase, the systematic latency with images matching (radargrams) is determined. In the final and most important phase of the procedure, the integration of a series of standard processing of GPR signals with the support of advanced algorithms for signal processing results of GPR observations have been interpreted and visualized. The testing pools, into which all of today’s important utilities have been buried, are a good approximation of pavement structures of regional and local roads as well as pedestrian precincts made on the basis of applicable technical specifications for pavement structure planning. Using all known data of the dimensions and buried utilities materials, pavement materials, pavement thickness, sub-base and subgrade, laboratory controlled dielectric, volume percentage of water content, geodetic measurements and considering method used in testing pools as given reference values, accuracy and precision of the proposed model have been analyzed in recording underground utilities infrastructure. The proposed model obtained in testing pools was further on tested in two selected areas of real urban environment. The results have shown that it is possible on the basis of optimum composed model to obtain information on dimensions, depth, inclination and position of ducts, pipes and cables in various demanding circumstances of urban environment subject to thickness and composition of pavement structure and the presence of uncontrolled variables of natural environment such as moisture and permittivity. It is realistic to expect average decimetre position (2D) and height accuracy. Important additional element is also three dimensional visualization of utility infrastructure based on the proposed model. The proposed model of GPR observations and/or research of recording utilities infrastructure, as presented in the thesis, is the first such research carried out in the territory of Slovenia. Moreover, the testing environment with all of its elements of real urban environment in the shape of testing pools has been created for the purpose of the present thesis and is as such unique and one among the few in the world. In the future, more active role in the matter of GPR observations for monitoring and recording utilities infrastructure may be expected.
机译:实施无损记录方法的必要性源于我们长期的实践经验,在建立,管理和维护斯洛文尼亚共和国公共基础设施统一地籍方面非常广泛的解决方案以及我们的记录基础设施领域的日常工作,包括公共事业,能源基础设施和通信设施。现在在世界其他地方也可能观察到类似趋势。本文设计并提出了一种基于可控测试池环境的地埋雷达监视地下公用设施的监测方法,并提出了一个三阶段过程。在第一阶段,介绍了定位GPR的运动学方法,并连接了地球物理和大地观测组。在第二阶段,确定具有图像匹配(雷达图)的系统延迟。在该程序的最后也是最重要的阶段,已经对GPR信号的一系列标准处理与高级算法(对GPR观测信号处理结果的支持)的集成进行了解释和可视化。如今所有重要的公用设施都已埋入其中的测试池,可以很好地近似区域和当地道路的路面结构,以及根据适用的路面结构规划技术规范制成的行人专用区。使用所有已知的尺寸和埋藏公用设施材料,路面材料,路面厚度,路基和路基,实验室控制的电介质,含水量百分比,大地测量结果以及将测试池中使用的方法作为给定的参考值,精度和在记录地下公用设施的基础上分析了所提出模型的精度。在测试池中获得的建议模型在两个选定的实际城市环境区域中进行了进一步测试。结果表明,在最佳组合模型的基础上,可以获得有关路面结构的厚度和成分以及存在与否的各种苛刻城市环境下管道,管道和电缆的尺寸,深度,倾斜度和位置的信息。自然环境的不受控制的变量,例如湿度和介电常数。期望平均分米位置(2D)和高度精度是现实的。重要的附加元素也是基于所提出的模型的公用事业基础设施的三维可视化。论文中提出的建议的GPR观测模型和/或记录公用设施基础设施研究是在斯洛文尼亚境内进行的首次此类研究。此外,出于本论文的目的,已经创建了具有测试池形状的真实城市环境的所有要素的测试环境,它是独一无二的,并且是世界上为数不多的环境之一。将来,可以预期在GPR观测方面将发挥更积极的作用,以监控和记录公用事业基础设施。

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    Šarlah Nikolaj;

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  • 年度 2016
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