Nondestructive millimeter-scale void detection for thick steel-shell–concrete interface of immersed tube tunnel: case study

IF 5.7 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Structural Health Monitoring-An International Journal Pub Date : 2023-07-05 DOI:10.1177/14759217231181419
Song-hui Li, Guoqing Liu, Yan Zhang, Hongbo Zhao, S. Feng, Fanzi Wu
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引用次数: 1

Abstract

The structural form of sandwich-structured immersed tunnel (SSIT) can be complex. During the casting of self-compacting concrete, creating void defects between the steel shell and concrete interface is not difficult, which can adversely affect the overall safety and service life of the structure. However, detecting millimeter-scale voids covered by a thick steel plate is a technical challenge for current engineering industries. In this study, we proposed a nondestructive millimeter-scale void detection method for SSITs with thick steel shells by combining impact imaging and neutron methods. First, based on the near-source wavefield theory and count rate of thermal neutrons, the void area and depth calculation methods were derived theoretically, and then the coupling detection method and grading criteria for void severity were proposed. Additionally, the void detection performance was validated for a full-scale SSIT model test by blind detection. Finally, the proposed method was applied to the SSIT of the Shenzhen–Zhongshan bridge. The results showed that the proposed method could quantitatively determine the location and distribution pattern of a void; however, it could not accurately determine the void depth. In contrast, the neutron method could accurately calculate the void depth but had a large minimum detectable unit area. The proposed method could effectively compensate for the limitations of both methods. Statistically, the coincidence rate of the model test was 95%, 89%, and 87.5% for the void location, void area, and void depth, respectively, when the error range was ±2 mm. Using this method, 30 tubes in the Shenzhen–Zhongshan bridge were inspected, and by summarizing the void law, suggestions to improve the casting process were proposed, such as adjusting the casting speed. Meanwhile, the void probability decreased significantly. The proposed method provides an important basis for high-quality construction in SSIT projects.
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沉管隧道厚钢壳-混凝土界面毫米级孔隙无损检测实例研究
夹层结构沉管隧道(SSIT)的结构形式可能很复杂。在自密实混凝土浇筑过程中,在钢壳和混凝土界面之间产生空隙缺陷并不困难,这会对结构的整体安全和使用寿命产生不利影响。然而,检测厚钢板覆盖的毫米级空隙对当前工程行业来说是一项技术挑战。在这项研究中,我们提出了一种结合冲击成像和中子方法的厚钢壳SSIT毫米级无损孔隙检测方法。首先,基于近源波场理论和热中子计数率,从理论上推导了空洞面积和深度的计算方法,然后提出了空洞严重程度的耦合检测方法和分级标准。此外,通过盲检测对全尺寸SSIT模型试验的空隙检测性能进行了验证。最后,将该方法应用于深圳-中山大桥的SSIT。结果表明,该方法可以定量地确定孔隙的位置和分布模式;然而,它不能准确地确定孔隙深度。相比之下,中子法可以准确地计算孔隙深度,但具有较大的最小可检测单位面积。所提出的方法可以有效地弥补这两种方法的局限性。从统计数据来看,当误差范围为±2时,模型试验的空隙位置、空隙面积和空隙深度的符合率分别为95%、89%和87.5% 采用该方法对深圳-中山大桥的30根钢管进行了检测,并通过总结空隙规律,提出了改进铸造工艺的建议,如调整铸造速度。同时,空隙率显著降低。该方法为SSIT项目的高质量施工提供了重要依据。
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来源期刊
CiteScore
12.80
自引率
12.10%
发文量
181
审稿时长
4.8 months
期刊介绍: Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
期刊最新文献
Deep learning-based obstacle-avoiding autonomous UAVs with fiducial marker-based localization for structural health monitoring. Deep learning-based concrete defects classification and detection using semantic segmentation. Combination of active sensing method and data-driven approach for rubber aging detection Distributed fiber optic strain sensing for crack detection with Brillouin shift spectrum back analysis An unsupervised transfer learning approach for rolling bearing fault diagnosis based on dual pseudo-label screening
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