Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes
Slope failure and debris flow cause lots of casualties and property loss. An early-warning system for slope collapse and debris flow is essential to ensure safety of human beings and assets. Based on fiber optic sensing technology and Internet of Things, a new sensing transducer for internal earth p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8101469/ |
| _version_ | 1818617326088486912 |
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| author | Dong-Sheng Xu Long-Jun Dong Lalit Borana Hua-Bei Liu |
| author_facet | Dong-Sheng Xu Long-Jun Dong Lalit Borana Hua-Bei Liu |
| author_sort | Dong-Sheng Xu |
| collection | DOAJ |
| description | Slope failure and debris flow cause lots of casualties and property loss. An early-warning system for slope collapse and debris flow is essential to ensure safety of human beings and assets. Based on fiber optic sensing technology and Internet of Things, a new sensing transducer for internal earth pressure measurement in a soil slope is proposed, fabricated, and tested in this paper. The working principles, theoretical analysis, laboratory calibrations, and discussions of the proposed pressure transducers are elaborated. Extensive evaluations of the resolutions, physical properties, and response to the applied pressures have been performed through modeling and experimentations. The results show that the sensitivity of the designed pressure sensor is 0.1287 kPa/με across a pressure range of 140 kPa. Finally, a field soil slope was instrumented with the developed fiber optic sensors and other sensors. Through internet and cloud computing platform, the stability of the soil slope was analyzed. In the cloud computing platform, the numerical simulation is carried out by considering the slope internal deformations, rainfall infiltration, and limit force equilibrium. The factor of safety of the soil slope was calculated, which could be used to determine health condition of the instrumented slope. The performance was evaluated and classified into three categories. It proves that the proposed early-warning system has potential to monitor the health condition of the soil slopes. |
| first_indexed | 2024-12-16T17:03:55Z |
| format | Article |
| id | doaj.art-c95f44b1860b46079606af31a72419fe |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:03:55Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c95f44b1860b46079606af31a72419fe2022-12-21T22:23:38ZengIEEEIEEE Access2169-35362017-01-015254372544410.1109/ACCESS.2017.27714948101469Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil SlopesDong-Sheng Xu0https://orcid.org/0000-0002-5586-8478Long-Jun Dong1https://orcid.org/0000-0002-4085-2975Lalit Borana2Hua-Bei Liu3School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha, ChinaDepartment of Civil Engineering, IIT Indore, Indore, IndiaSchool of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, ChinaSlope failure and debris flow cause lots of casualties and property loss. An early-warning system for slope collapse and debris flow is essential to ensure safety of human beings and assets. Based on fiber optic sensing technology and Internet of Things, a new sensing transducer for internal earth pressure measurement in a soil slope is proposed, fabricated, and tested in this paper. The working principles, theoretical analysis, laboratory calibrations, and discussions of the proposed pressure transducers are elaborated. Extensive evaluations of the resolutions, physical properties, and response to the applied pressures have been performed through modeling and experimentations. The results show that the sensitivity of the designed pressure sensor is 0.1287 kPa/με across a pressure range of 140 kPa. Finally, a field soil slope was instrumented with the developed fiber optic sensors and other sensors. Through internet and cloud computing platform, the stability of the soil slope was analyzed. In the cloud computing platform, the numerical simulation is carried out by considering the slope internal deformations, rainfall infiltration, and limit force equilibrium. The factor of safety of the soil slope was calculated, which could be used to determine health condition of the instrumented slope. The performance was evaluated and classified into three categories. It proves that the proposed early-warning system has potential to monitor the health condition of the soil slopes.https://ieeexplore.ieee.org/document/8101469/Fiber optic sensorInternet of Thingcloud computingearly-warning systemslope |
| spellingShingle | Dong-Sheng Xu Long-Jun Dong Lalit Borana Hua-Bei Liu Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes IEEE Access Fiber optic sensor Internet of Thing cloud computing early-warning system slope |
| title | Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes |
| title_full | Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes |
| title_fullStr | Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes |
| title_full_unstemmed | Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes |
| title_short | Early-Warning System With Quasi-Distributed Fiber Optic Sensor Networks and Cloud Computing for Soil Slopes |
| title_sort | early warning system with quasi distributed fiber optic sensor networks and cloud computing for soil slopes |
| topic | Fiber optic sensor Internet of Thing cloud computing early-warning system slope |
| url | https://ieeexplore.ieee.org/document/8101469/ |
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