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Geo-Sensing and Geo-Big Data
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Geo-Sensing and Geo-Big Data

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 7054

Special Issue Editors

Prof. Dr. Bin Shi

E-Mail Website
Guest Editor
School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
Interests: geo-engineering sensing technology; optical fiber sensing; sensing optical cable; FOS monitoring system
Dr. Gang Cheng

E-Mail Website
Guest Editor
School of Computer Science, North China Institute of Science and Technology, Beijing 101601, China
Interests: geotechnical engineering monitoring based on distributed fiber optic sensing technology; remote data acquisition; geological disaster evaluation based on the Internet of Things
Special Issues, Collections and Topics in MDPI journals
Dr. Jinghong Wu

E-Mail Website
Guest Editor
School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215011, China
Interests: geotechnical engineering monitoring and evaluation, and structural health monitoring based on distributed optical fiber sensing technology
Dr. Lei Gao

E-Mail Website
Guest Editor
Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing 210098, China
Interests: new technology of intelligent monitoring and testing of rock and soil mass, research and application of new pile foundation technology, and intelligent construction technology of geotechnical engineering

Special Issue Information

Dear Colleagues,

Fiber optic sensing can be turned into a 'nerve' to realize geo-sensing so as to mitigate geological and geotechnical disasters. Big data and artificial intelligence help to further realize from the perception to cognition of geoscience.

This Special Issue plans to give an overview of the most recent advances in the field of geo-sensing based on fiber optic sensing technologies and the application of big data for opto-electronic monitoring. This Special Issue is aimed at providing selected contributions on advances in the theory, experimentation, and application of fiber optic sensing in geological and geotechnical engineering monitoring.

The focus of this Special Issue is on presenting the latest advances in geo-sensing and geo-big data. Potential topics include, but are not limited to:

  • Advances in sensors and sensing technologies (DSS, DTS, DAS, FBG, MEMS, remote sensing, UVA, GPS, wireless sensor, chemosensor, etc.);
  • Opto-electronic monitoring in geo-engineering (geohazards, infrastructures, dams, mines, embankments, tunnels, underground space, etc.);
  • Opto-electronic monitoring in energy (geothermal, wind, hydrogen, solar, nuclear, shale gas, fossil, etc.);
  • Artificial intelligence algorithm in geological and geotechnical engineering monitoring;
  • Geo-big data and risk assessment of geotechnical engineering monitoring;
  • Fine monitoring technology of urban underground space;
  • Intelligent monitoring and maintenance of long-distance transportation infrastructure;
  • Monitoring practice and typical case analysis of major geotechnical engineering;
  • Intelligent real-time monitoring technology for linear engineering;
  • Smart geotechnical and resilient city.

Prof. Dr. Bin Shi
Dr. Gang Cheng
Dr. Jinghong Wu
Dr. Lei Gao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (4 papers)

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Research

13 pages, 5475 KiB  
Communication
Stress Monitoring of Segment Structure during the Construction of the Small-Diameter Shield Tunnel
by Liang Ding, Yi-Jie Sun, Wen-Zhi Zhang, Gang Bi and Hong-Zhong Xu
Sensors 2023, 23(19), 8023; https://doi.org/10.3390/s23198023 - 22 Sep 2023
Cited by 2 | Viewed by 1177
Abstract
Segmental stress during the construction process plays a pivotal role in assessing the safety and quality of shield tunnels. Fiber Bragg grating (FBG) sensing technology has been proposed for tunnel segment stress monitoring. A laboratory test was conducted to validate the reliable strain [...] Read more.
Segmental stress during the construction process plays a pivotal role in assessing the safety and quality of shield tunnels. Fiber Bragg grating (FBG) sensing technology has been proposed for tunnel segment stress monitoring. A laboratory test was conducted to validate the reliable strain measurement of FBG sensors. The field in situ monitoring of a sewerage shield tunnel was carried out to examine the longitudinal and circumferential stresses experienced by the segments throughout the construction phase. The cyclic fluctuations in stress were found to be synchronized with the variations in shield thrust. A comparison was made between the longitudinal and circumferential stress variations observed during the shield-driving and segment-assembly processes. Additionally, the time required for the grouting to reach its full curing strength was estimated, revealing its impact on the stress levels and range of the pipe segment. The findings of this study offer an enhanced understanding of the stress state and health condition of small-diameter shield tunnels, which can help in optimizing the design and construction process of tunnel segments, as well. Full article
(This article belongs to the Special Issue Geo-Sensing and Geo-Big Data)
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16 pages, 6506 KiB  
Article
Strain Transfer Mechanism in Surface-Bonded Distributed Fiber Optic Sensors under Different Strain Fields
by Wenbo Du, Xing Zheng, Bin Shi, Mengya Sun, Hao Wu, Weida Ni, Zhenming Zheng and Meifeng Niu
Sensors 2023, 23(15), 6863; https://doi.org/10.3390/s23156863 - 2 Aug 2023
Cited by 3 | Viewed by 1180
Abstract
Mastering the strain transfer mechanism in distributed fiber optic (DFO) sensors holds the key to analyzing strain measurement errors from DFO sensing systems. However, the impact of the monitored structure’s strain distribution on the strain transfer mechanism in DFO sensors has often been [...] Read more.
Mastering the strain transfer mechanism in distributed fiber optic (DFO) sensors holds the key to analyzing strain measurement errors from DFO sensing systems. However, the impact of the monitored structure’s strain distribution on the strain transfer mechanism in DFO sensors has often been overlooked in the existing research. To address this issue, a strain transfer model of surface-bonded DFO sensors with multilayered structures was established based on the shear lag theory. The closed-form solutions of the strain transfer coefficient of DFO sensors subjected to uniform, parabolic, single-linear gradient, and bilinear gradient strains were obtained. With a high-accuracy optical frequency-domain reflectometer (OFDR), the theoretical model was validated by laboratory tests. Upon parametric analysis, suggestions were further offered about designing and installing DFO sensors. Full article
(This article belongs to the Special Issue Geo-Sensing and Geo-Big Data)
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17 pages, 9335 KiB  
Article
Research on a Space–Time Continuous Sensing System for Overburden Deformation and Failure during Coal Mining
by Gang Cheng, Zhenxue Wang, Bin Shi, Wu Zhu and Tianbin Li
Sensors 2023, 23(13), 5947; https://doi.org/10.3390/s23135947 - 27 Jun 2023
Cited by 5 | Viewed by 1514
Abstract
Underground coal mining can cause the deformation, failure, and collapse of the overlying rock mass of a coal seam. If the mining design, monitoring, early warning, or emergency disposal are improper, in that case, it can often lead to mining disasters such as [...] Read more.
Underground coal mining can cause the deformation, failure, and collapse of the overlying rock mass of a coal seam. If the mining design, monitoring, early warning, or emergency disposal are improper, in that case, it can often lead to mining disasters such as roof falls, water inrush, surface collapse, and ground fissures, seriously threatening the safety of mine engineering and the geological environment protection in mining areas. To ensure the intrinsic security of the entire coal mining process, aspace–time continuous sensing system of overburden deformation and failure was developed, which breaks through the limitations of traditional monitoring methods that characterize the evolution process of overlying rock deformation and ground subsidence. This paper summarizes the classification of typical overburden deformation and failure modes. It researches the space–time continuous sensing of rock–soil mass above the coal seam based on Distributed Fiber Optic Sensing (DFOS). A multi-range strain optical fiber sensing neural series from micron to meter was developed to achieve synchronous sensing of overburden separation, internal micro–cracks, and large rock mass deformation. The sensing cable–rock mass coupling test verified the reliability of the optical fiber monitoring data. The sensing neural network of overburden deformation was constructed using integrated optical fiber layout technology on the ground and underground. Different sensing nerves’ performance and application effects in overburden deformation and failure monitoring were compared and analyzed with field monitoring examples. A physical model was used to carry out the experimental study on the overburden subsidence prediction during coal mining. The results showed that the optical fiber monitoring data were reliable and could be used to predict overburden subsidence. The reliability of the calculation model for overlying rock subsidence based on space–time continuous optical fiber sensing data was verified in the application of mining subsidence evaluation. A systematic review of the shortcomings of current overburden deformation observation technology during coal mining was conducted, and a space–time continuous sensing system for overburden deformation and failure was proposed. This system integrated sensing, transmission, processing, early warning, decision-making, and emergency response. Based on the fusion of multi-parameter sensing, multi-method transmission, multi-algorithm processing, and multi-threshold early warning, the system realized the real-time acquisition of space–time continuous information for the overburden above coal seams. This system utilizes long-term historical monitoring data from the research area for data mining and modeling, realizing the prediction and evaluation of the evolution process of overburden deformation as well as the potential for mining subsidence. This work provides a theoretical reference for the prevention and control of mining disasters and the environmental carrying capacity evaluation of coal development. Full article
(This article belongs to the Special Issue Geo-Sensing and Geo-Big Data)
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15 pages, 3677 KiB  
Article
Improvement and Performance Evaluation of a Dual-Probe Heat Pulse Distributed Temperature Sensing Method Used for Soil Moisture Estimation
by Jun-Cheng Yao, Bin Shi, Jie Liu, Meng-Ya Sun, Ke Fang, Jian Yao, Kai Gu, Wei Zhang and Ji-Wen Zhang
Sensors 2022, 22(19), 7592; https://doi.org/10.3390/s22197592 - 7 Oct 2022
Cited by 2 | Viewed by 1887
Abstract
Large-scale measurements of soil moisture play a critical role in many fields, such as agriculture, hydrology, and engineering. The distributed temperature sensing (DTS) technology, based on a dual-probe heat pulse (DPHP), is a novel approach to realizing large-scale soil moisture estimation. However, the [...] Read more.
Large-scale measurements of soil moisture play a critical role in many fields, such as agriculture, hydrology, and engineering. The distributed temperature sensing (DTS) technology, based on a dual-probe heat pulse (DPHP), is a novel approach to realizing large-scale soil moisture estimation. However, the application of the method is limited by the complex optical cable layout, calculation algorithm, and lack of standardized heating strategy. In this paper, an improved DPHP-DTS method considering the soil bulk density was proposed. The measurement accuracy of the DPHP-DTS method under different heating strategies was studied in laboratory experiments, and its long-term stability in regard to the monitoring of soil moisture during natural evaporation in different soils was tested. The results show that the improved DPHP-DTS method can accurately measure the soil moisture, and the fitting algorithm can reduce the error caused by the accuracy of the DTS temperature measurement under the low-power heating strategy. Its measurement accuracy increases with the increase in the heating strength and duration. In addition, the improved DPHP-DTS method can describe soil evaporation in both sand and loess with good reliability and stability. Full article
(This article belongs to the Special Issue Geo-Sensing and Geo-Big Data)
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