基于弹性波映像识别法的钢管隧洞缺陷检测

doi:10.3969/j.issn.1674-0696.2022.08.10

重庆交通大学学报（自然科学版） ›› 2022, Vol. 41 ›› Issue (08): 67-72.DOI: 10.3969/j.issn.1674-0696.2022.08.10

基于弹性波映像识别法的钢管隧洞缺陷检测

武鹏，袁刚烈，车爱兰

(上海交通大学船舶海洋与建筑工程学院，上海 200040)

收稿日期:2021-04-01 修回日期:2022-07-04 发布日期:2022-08-19
作者简介:武鹏(1997—)，男，山西大同人，博士研究生，主要从事岩土工程测试技术相关研究。E-mail：wp1129299745@sjtu.edu.cn 通信作者：车爱兰(1969—)，女，上海人，教授，博士，主要从事岩土工程测试研究方面的工作。E-mail：alche@sjtu.edu.cn
基金资助:
国家重点研发计划项目(2018YFC1504504)

Defect Detection of Steel Tube Tunnel Based on Elastic Wave Image Recognition Method

WU Peng, YUAN Ganglie, CHE Ailan

(School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University, Shanghai 200040, China)

Received:2021-04-01 Revised:2022-07-04 Published:2022-08-19

摘要/Abstract

摘要： 针对钢管隧洞的结构特征及缺陷的模式化特性，基于弹性波在层状介质中的传播特性，以弹性波响应能量E作为评价指标，利用模式识别中的聚类分析方法，对弹性波响应能量进行了k-means聚类分析，以聚类分析的结果为阈值对缺陷模式进行了评价；以某钢管隧洞出现明显变形的22 m长区域为研究对象，布设测点，采用3D扫描测量及弹性波测试，对测得的缺陷处弹性波信号进行了聚类分析，划分响应能量阈值对脱空区域进行识别，评价了钢管内壁的变形特性。研究表明：钢管隧洞缺陷随机分布，部分缺陷联通形成大片病害区；缺陷区域的弹性波响应明显放大；弹性波信号响应能量聚类分析评价结果与3D扫描结果一致性较好，验证了弹性波映像识别法的有效性。

关键词: 隧道工程；弹性波映像识别方法；聚类分析；钢管隧洞；3D扫描

Abstract: In view of the structural characteristics of steel tube tunnels and the patterned characteristics of defects, based on the propagation characteristics of elastic waves in layered media, k-means clustering analysis was carried out on the response energy of elastic waves, which took the response energy of elastic waves E as the evaluation index and used the clustering analysis method in pattern recognition. And the defect pattern was evaluated with the result of clustering analysis as the threshold. The 22 meter long area of a steel tube tunnel with obvious deformation was taken as the research object, and the measuring points were arranged. 3D scanning measurement and elastic wave test were used to carry out the clustering analysis on the measured elastic wave signals at the defects. And the response energy threshold was divided to identify the void area, and the deformation characteristics of the inner wall of the steel pipe were evaluated. The research shows that defects in steel tube tunnels are randomly distributed, and some defects are connected to form a large disease area. The elastic wave response in the defect region is significantly amplified. The evaluation results of elastic wave signal response energy cluster analysis are in good agreement with 3D scanning results, which verifies the effectiveness of elastic wave image recognition method.

Key words: tunnel engineering; elastic wave image recognition method; cluster analysis; steel tube tunnel; 3D scanning

中图分类号:

U178

武鹏，袁刚烈，车爱兰. 基于弹性波映像识别法的钢管隧洞缺陷检测[J]. 重庆交通大学学报（自然科学版）, 2022, 41(08): 67-72.

WU Peng, YUAN Ganglie, CHE Ailan. Defect Detection of Steel Tube Tunnel Based on Elastic Wave Image Recognition Method[J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(08): 67-72.

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基于弹性波映像识别法的钢管隧洞缺陷检测

Defect Detection of Steel Tube Tunnel Based on Elastic Wave Image Recognition Method

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