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 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/ $\mu \varepsilon $ 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.

[1]  Guangjie Han,et al.  Analysis of Energy-Efficient Connected Target Coverage Algorithms for Industrial Wireless Sensor Networks , 2017, IEEE Transactions on Industrial Informatics.

[2]  Mohsen Guizani,et al.  A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks , 2016, IEEE Communications Surveys & Tutorials.

[3]  Guangjie Han,et al.  HySense: A Hybrid Mobile CrowdSensing Framework for Sensing Opportunities Compensation under Dynamic Coverage Constraint , 2017, IEEE Communications Magazine.

[4]  Mohsen Guizani,et al.  Green Routing Protocols for Wireless Multimedia Sensor Networks , 2016, IEEE Wireless Communications.

[5]  Xibing Li,et al.  Discriminant models of blasts and seismic events in mine seismology , 2016 .

[6]  Ran Liu,et al.  Internet of Things: Application and Prospect , 2017 .

[7]  Ginu Rajan Optical fiber sensors : advanced techniques and applications , 2015 .

[8]  Guangjie Han,et al.  Three Dimensional Comprehensive Analytical Solutions for Locating Sources of Sensor Networks in Unknown Velocity Mining System , 2017, IEEE Access.

[9]  K. Hill,et al.  Fiber Bragg grating technology fundamentals and overview , 1997 .

[10]  Xibing Li,et al.  Pre-Alarm System Based on Real-Time Monitoring and Numerical Simulation Using Internet of Things and Cloud Computing for Tailings Dam in Mines , 2017, IEEE Access.

[11]  Weileun Fang,et al.  Sensitivity improvement for CMOS-MEMS capacitive pressure sensor using double deformarle diaphragms with trenches , 2017, 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS).

[12]  Qida Zhao,et al.  Temperature-insensitive fiber Bragg grating liquid-level sensor based on bending cantilever beam , 2005, IEEE Photonics Technology Letters.

[13]  Xibing Li,et al.  Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression , 2015, Rock Mechanics and Rock Engineering.

[14]  Dong-Sheng Xu Development of two optical fiber sensing technologies and applications in monitoring geotechnical structures , 2014 .

[15]  Yiping Cui,et al.  Highly Sensitive Liquid-Level Sensor Based on Etched Fiber Bragg Grating , 2007, IEEE Photonics Technology Letters.

[16]  Kyung-Rak Sohn,et al.  Liquid-level monitoring sensor systems using fiber Bragg grating embedded in cantilever , 2009 .

[17]  S. Lee,et al.  Low-cost flexible pressure sensor based on dielectric elastomer film with micro-pores , 2016 .

[18]  Weileun Fang,et al.  Mechanical force-displacement transduction structure for performance enhancement of CMOS-MEMS pressure sensor , 2014, 2014 IEEE 27th International Conference on Micro Electro Mechanical Systems (MEMS).

[19]  E. Lewis,et al.  Feedback Stabilized Interrogation Technique for EFPI/FBG Hybrid Fiber-Optic Pressure and Temperature Sensors , 2012, IEEE Sensors Journal.

[20]  M SarathT,et al.  Level Measurement Using MEMS Pressure Sensor , 2013 .

[21]  E. Lewis,et al.  Fibre optic pressure and temperature sensor for geothermal wells , 2010, 2010 IEEE Sensors.

[22]  Weileun Fang,et al.  Development of a CMOS MEMS pressure sensor with a mechanical force-displacement transduction structure , 2015 .

[23]  Chun Cheung Lai,et al.  Development of Level Sensors Based on Fiber Bragg Grating for Railway Track Differential Settlement Measurement , 2016, IEEE Sensors Journal.

[24]  Elfed Lewis,et al.  A fibre optic sensor for the in situ determination of rock physical properties , 2012 .

[25]  R. Sabbaghi‐Nadooshan,et al.  Design and simulation of high sensitive capacitive pressure sensor with slotted diaphragm , 2012, 2012 International Conference on Biomedical Engineering (ICoBE).

[26]  Alex A. Kazemi,et al.  Fiber optical liquid level sensor under cryogenic environment , 2001, SPIE Optics East.

[27]  Leonardo Zan,et al.  Landslides early warning monitoring system , 2002, IEEE International Geoscience and Remote Sensing Symposium.