登录
注册
E-alert
登录
注册
E-alert
Research on Time-Difference and Fresnel Zone Inversion Method Based on Unstructured Grid in Bridge Inspection
-
摘要: 层析技术是一种桥梁无损检测的新兴技术,但是传统层析反演使用矩形网格来剖分模型,并且需要大量的检波设备来确保精确度。为改善桥梁层析检测的效果,在反演中引入了菲涅尔带技术,增大反演射线的覆盖范围,改善了检波设备不足导致的射线稀疏问题;利用时差法,提高了初至数据的准确性,减小了初至拾取误差在小尺度测量中的影响。此外使用了三角网格对桥梁模型进行剖分,比起矩形网格能够更好地贴合边缘不规则的桥梁模型。模型试算和实际测量的结果表明:菲涅尔带方法可以较好地反演出速度异常区的位置、形状和大小;对有拾取误差的数据使用时差法处理后,反演结果接近于准确数据的反演结果;该算法提升了反演的准确性,可以有效运用于桥梁检测项目中。Abstract: Computerized tomographic technique is a emerging technique for nondestructive bridge inspection. In conventional tomographic inversion, rectangular grid is used to divide the model, and a large number of detection equipment is required to ensure the accuracy. To improve the effect of bridge tomographic inspection, the technique of Fresnel zone was introduced into the inversion to enlarge the coverage range of the inversion ray, which improved the ray sparseness caused by insufficient inspection equipment. By using the time difference method, the accuracy of first arrival data was improved and the influence of the first arrivals pick-up error in small-scale measurement was reduced. In addition, triangular mesh was used to divide the bridge model, which could fit the bridge model with irregular edges better than rectangular mesh. The results of model trial calculation and actual measurement showed that the Fresnel zone method could better deduce the position, shape and size of the velocity anomaly area. After using the time difference method to deal with the data with picking errors, the inversion results were close to the inversion results of accurate data. The algorithm improved the accuracy of inversion and could be effectively applied in bridge inspection projects.
-
[1] 王一飞.公路桥梁检测技术及应用分析[J].四川建材,2020,46(10):28-29. [2] TAN L Y, ZHANG Z Y, WANG X. Research on design and application based on bridge inspection and maintenance scheme[J]. IOP Conference Series:Materials Science and Engineering, 2020, 914(1). [3] QI X. Improved algorithm based on block Iteration for ultrasonic computerized tomography on concrete[J]. Journal of Information&Computational Science, 2015, 12(11):4377-4384. [4] 张杰.光纤传感技术在桥梁检测中的运用[J].公路与汽运, 2016(2):203-204. [5] POURIA A, MAYRAI G, MARCO A, et al. A computer vision based rebar detection chain for automatic processing of concrete bridge deck GPR data[J]. Automation in Construction,2020,112. [6] LIN J J, IBRA A, SARWADE S, et al. Bridge Inspection with aerial robots:automating the entire pipeline of visual data capture, 3D mapping, defect detection, analysis, and reporting[J]. Journal of Computing in Civil Engineering,2021,35(2). [7] PENG X, ZHONG X G, ZHAO C, et al. The feasibility assessment study of bridge crack width recognition in images based on special Inspection UAV[J]. Advances in Civil Engineering,2020,2020. [8] 赵明阶,徐蓉.超声波CT成像技术及其在大型桥梁基桩无损检测中的应用[J].重庆交通学院学报,2001(2):73-77,86. [9] 谷昊.声波CT技术在桥梁无损检测中的应用[J].交通世界(建养.机械),2012(11):171-173. [10] 袁浩,唐英.弹性波(CT)层析技术在桥梁检测中的应用[J].山西建筑,2017,43(8):155-157. [11] LI B, LIU B, XU F, et al. Compressive sampling-based ultrasonic computerized tomography technique for damage detection in concrete-filled steel tube in a bridge[J]. International Journal of Distributed Sensor Networks, 2021, 17(2):1550147720986113. [12] 刘润泽,田清伟,于师建,等.结构混凝土三角网声波层析成像检测技术[J].地球物理学进展,2014,29(4):1907-1913. [13] 李旭,房鹏,祁勋,等.桥梁检测中非结构化网格层析正演算法研究[J].物探化探计算技术,2020, 42(1):50-55. [14] 周建宇.井间地震研究与应用[D].兰州:中国科学院研究生院(兰州地质研究所),2002. [15] 刘双.反射菲涅尔带走时层析反演方法研究[D].青岛:中国石油大学(华东),2016. [16] 李亭,宋炜,王泉栋.基于时差法的微地震速度反演[C]//中国地球科学联合学术年会:专题20:岩石物理与非常规油气勘探开发论文集. 2014. [17] 缪思钰,张海江,陈余宽,等.基于微地震定位和速度成像的页岩气水力压裂地面微地震监测[J].石油物探,2019, 58(2):262-271,284. 期刊类型引用(4)
1. 张斗中，陈孔全，汤济广，庹秀松，马帅. 鄂西荆门地区志留系龙马溪组古构造应力场研究及裂缝预测. 地球学报. 2024(02): 217-231 . 
百度学术2. 卓志权，利铭，佟安，张军徽. 含孔洞红砂岩破坏机理的离散元研究. 科技和产业. 2023(05): 159-165 . 百度学术3. 陈绍杰，李法鑫，尹大伟，张继成. 不同高比灰岩-煤组合体变形破坏特征实验研究. 中南大学学报(自然科学版). 2023(06): 2459-2472 . 百度学术4. 利铭，卓志权，张军徽. 基于应变场的卷积神经网络岩石裂缝识别方法. 煤炭科技. 2023(05): 17-23 . 百度学术其他类型引用(5)
-
点击查看大图
计量
- 文章访问数: 117
- HTML全文浏览量: 27
- PDF下载量: 2
- 被引次数: 9
下载:
