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旧有隧道隐伏病害GPR探测异常特征分析及病害程度评价
引用本文:李宁,刘振东,郭秀军,王莹莹.旧有隧道隐伏病害GPR探测异常特征分析及病害程度评价[J].长江科学院院报,2018,35(3):97-103.
作者姓名:李宁  刘振东  郭秀军  王莹莹
作者单位:1.中国海洋大学 环境科学与工程学院,山东 青岛 266100;2.山东省城乡建设勘察设计研究院,济南 250031
基金项目:国家自然科学基金重大科研仪器研制项目,国家重点研发项目,国家自然科学基金项目
摘    要:旧有隧道隐伏病害复杂多样,持续演变会对隧道结构与行车安全造成危害。虽然探地雷达技术(GPR)在隐伏病害调查中已应用广泛,但对GPR异常特征的认识并未统一,相应病害程度评价体系亦未建立。为进一步推动技术发展,归纳总结不同成因旧有隧道病害,建立相应介电模型,正演得到GPR理论图像并与工程实测图像对比,进行异常特征甄别;引入模糊数学的隶属度理论将多个因素进行综合评判,建立旧有隧道病害程度评判体系。研究表明:隧道衬砌裂缝和空洞会因填充介质不同,介电常数差异显著,多表现为同相轴错断或者局部性绕射增强的异常特征;衬砌非密实区和防渗层破坏区会持续发展成水-混凝土-残积物混合群块结构,具有多个反射界面,相应GPR图像波形杂乱,并伴有局部强反射。应用实例显示利用GPR诊测确定潜在病害区域后,在核定与旧有隧道隐伏病害相适宜的评价权重基础上,以建立的评价模型将多因素制约对象进行隶属度综合评判,能够较好地开展旧有隧道安全等级划分。

关 键 词:旧有隧道  隐伏病害  探地雷达  异常特征  病害评判体系  
收稿时间:2017-09-19

Analysis and Evaluation of Hidden Diseases in Old Tunnel with GPR Images
LI Ning,LIU Zhen-dong,GUO Xiu-jun,WANG Ying-ying.Analysis and Evaluation of Hidden Diseases in Old Tunnel with GPR Images[J].Journal of Yangtze River Scientific Research Institute,2018,35(3):97-103.
Authors:LI Ning  LIU Zhen-dong  GUO Xiu-jun  WANG Ying-ying
Affiliation:1.College of Environmental Science and Engineering,Ocean University of China,Qingdao 266100,China;2.Shandong Urban and Rural Construction Survey and Design Institute,Jinan 250031,China
Abstract:The worsening of hidden diseases of old tunnel,which are of variety and complexity,would cause harm to tunnel structure and traffic safety. Although ground penetrating radar (GPR) technology has been widely appliedto the investigation of hidden diseases, no uniform understanding or systematic conclusion of anomaly features inGPR images has been reached. In this article we sum up the types and causes of old tunnel diseases, and set upcorresponding earth-electricity models to identify anomaly features through forward modeling and comparing theGPR images with field measurements. Moreover, we establish an evaluation system for old tunnel disease by introducingthe concept of membership degree in fuzzy mathematics. Results show that the dielectric constants of liningcrack and cavity are significantly different due to different filling mediums, reflected by event dislocation and localimprovement of diffraction patterns. The non-compacted and impervious layer gradually develops into a mixed structureinvolving water, concrete, and residues with multiple reflection interfaces, and the corresponding GPR imageis cluttered with local strong reflection. Application practice prove that the presented model could well assess thesafety levels of old tunnels based on GPR detection of potential disease areas.
Keywords:old tunnel  hidden diseases  ground penetrating radar (GPR)  anomaly features  disease evaluation system  
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