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结合多场信息的热红外遥感图像用于桩承式滑坡变形特征分析

Thermal Infrared Imagery Integrated with Multi-Field Information for Characterization of Pile-Reinforced Landslide Deformation.

作者信息

Zhou Chang, Ying Chunye, Hu Xinli, Xu Chu, Wang Qiang

机构信息

Faculty of Engineering, China University of Geosciences, Wuhan 430074, China.

出版信息

Sensors (Basel). 2020 Feb 20;20(4):1170. doi: 10.3390/s20041170.

DOI:10.3390/s20041170
PMID:32093335
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7070546/
Abstract

Physical model testing can replicate the deformation process of landslide stabilizing piles and analyze the pile-landslide interaction with multiple field information, thoroughly demonstrating its deformation and failure mechanism. In this paper, an integrated monitoring system was introduced. The instrumentation used included soil pressure cells, thermal infrared (TIR) imagery, 3D laser scanner, and digital photography. In order to precisely perform field information analysis, an index was proposed to analyze thermal infrared temperature captured by infrared thermography; the qualitative relationship among stress state and deformation as well as thermal infrared temperature is analyzed. The results indicate that the integrated monitoring system is expected to be useful for characterizing the deformation process of a pile-reinforced landslide. Difference value of TIR temperature () is a useful indicator for landslide detection, and its anomalies can be selected as a precursor to landslide deformation.

摘要

物理模型试验能够再现滑坡抗滑桩的变形过程,并通过多场信息分析桩与滑坡的相互作用,全面揭示其变形破坏机制。本文介绍了一种综合监测系统。所使用的仪器包括土压力盒、热红外(TIR)图像、三维激光扫描仪和数码摄影。为了精确地进行现场信息分析,提出了一个指标来分析红外热成像捕获的热红外温度;分析了应力状态、变形与热红外温度之间的定性关系。结果表明,该综合监测系统有望用于表征桩加固滑坡的变形过程。TIR温度差值()是滑坡检测的一个有用指标,其异常可作为滑坡变形的前兆。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/b290f8a3a6bc/sensors-20-01170-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/928d29e5ae2e/sensors-20-01170-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/894025ffbf7d/sensors-20-01170-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/99a27b8e7d9e/sensors-20-01170-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/4bb78b9cf053/sensors-20-01170-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/30e5a53c0117/sensors-20-01170-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/b290f8a3a6bc/sensors-20-01170-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/928d29e5ae2e/sensors-20-01170-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/894025ffbf7d/sensors-20-01170-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/99a27b8e7d9e/sensors-20-01170-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/4bb78b9cf053/sensors-20-01170-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/30e5a53c0117/sensors-20-01170-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/7070546/b290f8a3a6bc/sensors-20-01170-g006.jpg

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本文引用的文献

1
Thermal Infrared Imagery Integrated with Terrestrial Laser Scanning and Particle Tracking Velocimetry for Characterization of Landslide Model Failure.热红外图像与地面激光扫描和粒子追踪测速技术集成,用于滑坡模型破坏特性的描述。
Sensors (Basel). 2019 Dec 30;20(1):219. doi: 10.3390/s20010219.