衬砌结构异形富水微裂缝模型试验与量化识别
作者:
作者单位:

(长沙理工大学 土木工程学院,湖南 长沙 410114)

作者简介:

通讯作者:

凌同华(1968—),男,教授,主要从事城市轨道交通工程、隧道与地下工程、岩土工程灾害监测与控制等方面的研究工作。E-mail:lingtonghua@163.com

中图分类号:

U451

基金项目:

国家自然科学基金项目(5207081829)


Models test and quantitative identification of abnormal water-rich microcracks in lining structure
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(School of Civil Engineering, Changsha University of Science & Technology, Changsha 410114, China)

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    摘要:

    为探讨准确识别隧道衬砌结构中异形富水微裂缝的方法,用探地雷达和F-K偏移法针对4种异形富水微裂缝模型进行检测试验及对雷达检测的特征信号进行偏移归位,再用波形分析法和小波变换模极大值法对裂缝模型的位置和形态进行识别。研究结果表明:异形富水微裂缝模型的雷达响应图像很难被直接识别,通过F-K偏移归位处理后,可识别裂缝模型的形态。小波变换模极大值法比波形分析法能更精确地实现异形富水微裂缝模型的量化识别;微裂缝模型的二维轮廓重构图能够较好地拟合实体模型的形状。该结果可为隧道衬砌结构异形富水微裂缝的识别提供借鉴。

    Abstract:

    To investigate the identification of special-shaped water-rich micro-cracks in tunnel lining structures, ground-penetrating radar (GPR) was used to detect the water-filling models of four special-shaped micro-cracks. The F-K migration method was applied to offset and locate the radar characteristic signals of micro-cracks, with crack locations identified through waveform analysis and the wavelet modulus maximum algorithm. The results indicate that the radar response images of irregular micro-cracks are difficult to identify directly, while their morphology can be highlighted by the F-K migration method. Compared to waveform analysis, the wavelet modulus maximum algorithm provides more accurate positioning and identification of irregular micro-cracks. The two-dimensional contour reconstruction of the micro-fracture models fits the shape of the solid models. The research results provide a foundational basis for the identifying abnormal water-rich micro-cracks in tunnel lining structures.

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引用本文

娄玉鹏,凌同华,何文超,等.衬砌结构异形富水微裂缝模型试验与量化识别[J].交通科学与工程,2024,40(3):74-81.
LOU Yupeng, LING Tonghua, HE Wenchao, et al. Models test and quantitative identification of abnormal water-rich microcracks in lining structure[J]. Journal of Transport Science and Engineering,2024,40(3):74-81.

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  • 收稿日期:2022-03-07
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  • 在线发布日期: 2024-06-26
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