期刊
NATURAL HAZARDS
卷 109, 期 3, 页码 2557-2573出版社
SPRINGER
DOI: 10.1007/s11069-021-04932-1
关键词
Real-time monitoring; Subsurface deformation; Wireless sensor network; Ultra-weak fiber Bragg gratings
资金
- National Natural Science Foundation of China [42030701, 41977217, 41427801]
- Natural Science Foundation of Jiangsu Province [BK20200217]
- China Scholarship Council [201906190153]
The study introduces a novel fiber-optic wireless sensor network method for real-time monitoring of subsurface deformation, successfully applied in field measurements in Cangzhou, China. The results demonstrate the accuracy of the technology in capturing subsurface deformation development and offering solutions for better understanding the subsurface deformation mechanism.
The determination of subsurface deformation is critical to understanding the subsurface dynamic processes, but most of conventional monitoring methods still have challenges in remotely obtaining detailed data. Herein, a novel fiber-optic wireless sensor network using the ultra-weak fiber Bragg gratings technique was proposed. It allows real-time remote capture of subsurface deformation along the fiber-optic cables. Such a fiber-optic measurement system was employed in a borehole to a depth of 340 m in Cangzhou, China. Strain profiles were measured monthly with a spatial resolution of 5 m and strain resolution of 1 mu epsilon, and the development of all strata deformation in the aquifer systems was calculated from January 2019 to December 2019. It turns out that the subsidence rate in this area is approximate 9 mm/a, which agrees well with the result of extensometer measurements. The significant strata compaction in the second aquifer and the third aquitard rapidly increased from May 2019 to July 2019, which could be attributed to the decline in groundwater. It is concluded that the fiber-optic wireless sensor network accurately captures subsurface deformation development and helps to better elucidate the subsurface deformation mechanism and provide solutions for the prevention and mitigation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据