The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system ...The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system with kilometer-level sensing distance and submeter spatial resolution.Based on this,we propose a Raman distributed optical fiber sensing scheme based on chaotic pulse cluster demodulation.Chaotic pulse clusters are used as the probe signal,in preference to conventional pulsed or chaotic single-pulse lasers.Furthermore,the accurate positioning of the temperature variety region along the sensing fiber can be realized using chaotic pulse clusters.The proposed demodulation scheme can enhance the signal-to-noise ratio by improving the correlation between the chaotic reference and the chaotic Raman anti-Stokes scattering signals.The experiment achieved a sensing spatial resolution of 30 cm at a distributed temperature-sensing distance of∼6.0 km.Furthermore,we explored the influence of chaotic pulse width and detector bandwidth on the sensing spatial resolution.In addition,the theoretical experiments proved that the sensing spatial resolution in the proposed scheme was independent of the pulse width and sensing distance.展开更多
Despite the extensive use of distributed fiber optic sensing(DFOS)in monitoring underground structures,its potential in detecting structural anomalies,such as cracks and cavities,is still not fully understood.To contr...Despite the extensive use of distributed fiber optic sensing(DFOS)in monitoring underground structures,its potential in detecting structural anomalies,such as cracks and cavities,is still not fully understood.To contribute to the identification of defects in underground structures,this study conducted a four-point bending test of a reinforced concrete(RC)beam and uniaxial loading tests of an RC specimen with local cavities.The experimental results revealed the disparity in DFOS strain spike profiles between these two structural anomalies.The effectiveness of DFOS in the quantification of crack opening displacement(COD)was also demonstrated,even in cases where perfect bonding was not achievable between the cable and structures.In addition,DFOS strain spikes observed in two diaphragm wall panels of a twin circular shaft were also reported.The most probable cause of those spikes was identified as the mechanical behavior associated with local concrete contamination.With the utilization of the strain profiles obtained from laboratory tests and field monitoring,three types of multi-classifiers,based on support vector machine(SVM),random forest(RF),and backpropagation neural network(BP),were employed to classify strain profiles,including crack-induced spikes,non-crack-induced spikes,and non-spike strain profiles.Among these classifiers,the SVM-based classifier exhibited superior performance in terms of accuracy and model robustness.This finding suggests that the SVM-based classifier holds promise as a potential solution for the automatic detection and classification of defects in underground structures during long-term monitoring.展开更多
Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their se...Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their service life is essential for the overall functionality of geotechnical infrastructure.Distributed Brillouin sensing(DBS)is increasingly applied in geotechnical projects due to its ability to acquire spatially continuous strain and temperature distributions over distances of up to 150 km using a single optical fibre.However,limited by the complex operations of distributed optic fibre sensing(DFOS)sensors in curved structures,previous reports about exploiting DBS in geotechnical structural health monitoring(SHM)have mostly been focused on flat surfaces.The lack of suitable DFOS installation methods matched to the spatial characteristics of continuous monitoring is one of the major factors that hinder the further application of this technique in curved structures.This review paper starts with a brief introduction of the fundamental working principle of DBS and the inherent limitations of DBS being used on monitoring curved surfaces.Subsequently,the state-of-the-art installation methods of optical fibres in curved structures are reviewed and compared to address the most suitable scenario of each method and their advantages and disadvantages.The installation challenges of optical fibres that can highly affect measurement accuracy are also discussed in the paper.展开更多
Phase-sensitive Optical Time-Domain Reflectometer(φ-OTDR)technology facilitates the real-time detection of vibration events along fiber optic cables by analyzing changes in Rayleigh scattering signals.This technology...Phase-sensitive Optical Time-Domain Reflectometer(φ-OTDR)technology facilitates the real-time detection of vibration events along fiber optic cables by analyzing changes in Rayleigh scattering signals.This technology is widely used in applications such as intrusion monitoring and structural health assessments.Traditional signal processing methods,such as Support Vector Machines(SVM)and K-Nearest Neighbors(KNN),have limitations in feature extraction and classification in complex environments.Conversely,a single deep learning model often struggles with capturing long time-series dependencies and mitigating noise interference.In this study,we propose a deep learning model that integrates Convolutional Neural Network(CNN),Long Short-Term Memory Network(LSTM),and Transformer modules,leveraging φ-OTDR technology for distributed fiber vibration sensing event recognition.The hybrid model combines the CNN's capability to extract local features,the LSTM's ability to model temporal dynamics,and the Transformer's proficiency in capturing global dependencies.This integration significantly enhances the accuracy and robustness of event recognition.In experiments involving six types of vibration events,the model consistently achieved a validation accuracy of 0.92,and maintained a validation loss of approximately 0.2,surpassing other models,such as TAM+BiLSTM and CNN+CBAM.The results indicate that the CNN+LSTM+Transformer model is highly effective in handling vibration signal classification tasks in complex scenarios,offering a promising new direction for the application of fiber optic vibration sensing technology.展开更多
Presented here is long-range distributed vibration sensing based on internal-modulation optical frequency domain reflectometry(OFDR).In the proposed system with internal modulation,a silicon-based photonic-chip laser i...Presented here is long-range distributed vibration sensing based on internal-modulation optical frequency domain reflectometry(OFDR).In the proposed system with internal modulation,a silicon-based photonic-chip laser is used as the laser source,and by controlling the output voltage curve of an arbitrary waveform generator to induce temperature change in the external cavity of the laser,a 10-GHz optical frequency tuning range is achieved.The complexity of the proposed internal-modulation system is lower than that of the traditional external-modulation OFDR system that combines a narrow-linewidth laser with a single-sideband modulator to achieve wavelength tuning.Cross-correlation analysis is used as a sensing mechanism to evaluate the similarity between Rayleigh scatter signals and to achieve vibration event localization.Experimental comparison is made of the vibration sensing performance of the external-and internal-modulation systems,and for a vibration event generated at a distance of 100.95 km,they locate it with a sensing spatial resolution of 43.0 m and 16.8 m,respectively.The results indicates that the proposed distributed vibration sensing based on internal modulation has better sensing performance and lower complexity compared to the traditional external-modulation system.In addition,the proposed system is single-ended and involves no optical amplification,which makes it very suitable for ultra-long-range sensing.展开更多
The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibratio...The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibration signals induced by external events and to effectively provide early warnings of potential intrusion activities.Due to the complexity and diversity of external intrusion events,traditional deep learning methods can achieve event recognition with an average accuracy exceeding 90%.However,these methods rely on large-scale datasets,leading to significant time and labor costs during the data collection process.Additionally,traditional methods perform poorly when faced with the scarcity of low-frequency event samples,making it challenging to address these rare occurrences.To address this issue,this paper proposes a small-sample learning model based on triplet learning for intrusion event recognition.The model employs a 6-way 20-shot support set configuration and utilizes the KNN clustering algorithm to assess the model's performance.Experimental results indicate that the model achieves an average accuracy of 91.6%,further validating the superior performance of the triplet learning model in classifying external intrusion events.Compared to traditional methods,this approach not only effectively reduces the dependence on large-scale datasets but also better addresses the classification of low-frequency event samples,demonstrating significant application potential.展开更多
This paper investigates the deformation and fracture propagation of sandstone specimen under uniaxial compression using the distributed fiber optic strain sensing(DFOSS)technology.It shows that the DFOSS-based circumf...This paper investigates the deformation and fracture propagation of sandstone specimen under uniaxial compression using the distributed fiber optic strain sensing(DFOSS)technology.It shows that the DFOSS-based circumferential strains are in agreement with the data monitored with the traditional strain gage.The DFOSS successfully scans the full-field view of axial and circumferential strains on the specimen surface.The spatiotemporal strain measurement based on DFOSS manifests crack closure and elastoplastic deformation,detects initialization of microcrack nucleation,and identifies strain localization within the specimen.The DFOSS well observes the effects of rock heterogeneity on rock deformation.The advantage of DFOSS-based strain acquisition includes the high spatiotemporal resolution of signals and the ability of full-surface strain scanning.The introduction to the DFOSS technology yields a better understanding of the rock damage process under uniaxial compression.展开更多
Confinement of rock bolts by the surrounding rock formation has long been recognized as a positive contributor to the pull-out behavior,yet only a few experimental works and analytical models have been reported,most o...Confinement of rock bolts by the surrounding rock formation has long been recognized as a positive contributor to the pull-out behavior,yet only a few experimental works and analytical models have been reported,most of which are based on the global rock bolt response evaluated in pull-out tests.This paper presents a laboratory experimental setup aiming to capture the rock formation effect,while using distributed fiber optic sensing to quantify the effect of the confinement and the reinforcement pull-out behavior on a more local level.It is shown that the behavior along the sample itself varies,with certain points exhibiting stress drops with crack formation.Some edge effects related to the kinematic freedom of the grout to dilate are also observed.Regardless,it was found that the mid-level response is quite similar to the average response along the sample.The ability to characterize the variation of the response along the sample is one of the many advantages high-resolution fiber optic sensing allows in such investigations.The paper also offers a plasticity-based hardening load transfer function,representing a"slice"of the anchor.The paper describes in detail the development of the model and the calibration/determination of its parameters.The suggested model captures well the coupled behavior in which the pull-out process leads to an increase in the confining stress due to dilative behavior.展开更多
We have numerically and experimentally investigated the flow rate measurement of the pipeline based on the optical fiber.Employing the large eddy simulation(LES)model,we have quantitatively analyzed the pressure fluct...We have numerically and experimentally investigated the flow rate measurement of the pipeline based on the optical fiber.Employing the large eddy simulation(LES)model,we have quantitatively analyzed the pressure fluctuation of the pipe wall caused by the turbulent flow in the pipeline.The simulation results have shown that the standard deviation of pressure fluctuation was quadratic with the flow rate.We have verified the theoretical model by using a distributed optical fiber acoustic sensing(DAS)system in the flow rate range from 0.61 m/s to 2.42 m/s.The experimental results were consistent with the simulation results very well.Furthermore,to improve the measuring error at the low flow rate,we have employed the composite adaptive denoising algorithm to eliminate the background noise and system noise.The final results have shown that the minimum goodness of fit was improved from 0.962 to 0.997,and the variation of the quadratic coefficient significantly decreased by 93.25%.The measured flow rate difference was only 0.84%between different sensing points in repeated experiments.展开更多
Underground mine pillars provide natural stability to the mine area,allowing safe operations for workers and machinery.Extensive prior research has been conducted to understand pillar failure mechanics and design safe...Underground mine pillars provide natural stability to the mine area,allowing safe operations for workers and machinery.Extensive prior research has been conducted to understand pillar failure mechanics and design safe pillar layouts.However,limited studies(mostly based on empirical field observation and small-scale laboratory tests)have considered pillar-support interactions under monotonic loading conditions for the design of pillar-support systems.This study used a series of large-scale laboratory compression tests on porous limestone blocks to analyze rock and support behavior at a sufficiently large scale(specimens with edge length of 0.5 m)for incorporation of actual support elements,with consideration of different w/h ratios.Both unsupported and supported(grouted rebar rockbolt and wire mesh)tests were conducted,and the surface deformations of the specimens were monitored using three-dimensional(3D)digital image correlation(DIC).Rockbolts instrumented with distributed fiber optic strain sensors were used to study rockbolt strain distribution,load mobilization,and localized deformation at different w/h ratios.Both axial and bending strains were observed in the rockbolts,which became more prominent in the post-peak region of the stress-strain curve.展开更多
Extensive urban areas worldwide face significant landslide hazards, impacting inhabitants, buildings, and critical infrastructures alike. In the case of slow-moving deep-seated landslides involving huge areas and char...Extensive urban areas worldwide face significant landslide hazards, impacting inhabitants, buildings, and critical infrastructures alike. In the case of slow-moving deep-seated landslides involving huge areas and characterized by complex patterns, when the cost of repairing infrastructures, relocating communities, and restoring cultural sites might be such that it is unsustainable for the community, the exposed structures require significant effort for their surveillance and protection, which can be supported by the development of innovative monitoring systems. For this purpose, a smart extenso-inclinometer, realized by equipping a conventional inclinometer tube with distributed strain and temperature transducers based on optical fiber sensing technology, is presented. In situ monitoring of the active deep-seated San Nicola landslide in Centola (Campania, southern Italy) demonstrated its ability to capture the main features of movements and reconstruct a tridimensional evolution of the landslide pattern, even when the entity of both vertical and horizontal soil strain components is comparable. Although further tests are needed to definitively ascertain the extensometer function of the new device, by interpreting the strain profiles of the landslide body and identifying the achievement of predetermined thresholds, this system could provide a warning of the trigger of a landslide event. The use of the smart extenso-inclinometer within an early warning system for slow-moving landslides holds immense potential for reducing the impact of landslide events.展开更多
Understanding the spatiotemporal evolution of overburden deformation during coal mining is still a challenge in engineering practice due to the limitation of monitoring techniques. Taking the Yangliu Coal Mine as an e...Understanding the spatiotemporal evolution of overburden deformation during coal mining is still a challenge in engineering practice due to the limitation of monitoring techniques. Taking the Yangliu Coal Mine as an example, a similarity model test was designed and conducted to investigate the deformation and failure mechanism of overlying rocks in this study. Distributed fiber optic sensing(DFOS), highdensity electrical resistivity tomography(HD-ERT) and close-range photogrammetry(CRP) technologies were used in the test for comprehensive analyses. The combined use of the three methods facilitates the investigation of the spatiotemporal evolution characteristics of overburden deformation, showing that the mining-induced deformation of overburden strata was a dynamic evolution process. This process was accompanied by the formation, propagation, closure and redevelopment of separation cracks.Moreover, the key rock stratum with high strength and high-quality lithology played a crucial role in the whole process of overburden deformation. There were generally three failure modes of overburden rock layers, including bending and tension, overall shearing, and shearing and sliding. Shear failure often leads to overburden falling off in blocks, which poses a serious threat to mining safety. Therefore, realtime and accurate monitoring of overburden deformation is of great significance for the safe mining of underground coal seams.展开更多
Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This pa...Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This paper presents an experimental study to evaluate the feasibility of fiber optic strain sensing nerves in sinkhole monitoring.Combining the artificial neural network(ANN)and particle image velocimetry(PIV)techniques,a series of model tests have been performed to explore the relationship between strain measurements and sinkhole development and to establish a conversion model from strain data to ground settlements.It is demonstrated that the failure mechanism of the soil above the sinkhole developed from a triangle failure plane to a vertical failure plane with increasing collapse volume.Meanwhile,the soil-embedded fiber optic strain sensing nerves allowed deformation monitoring of the ground soil in real time.Furthermore,the characteristics of the measured strain profiles indicate the locations of sinkholes and the associated shear bands.Based on the strain data,the ANN model predicts the ground settlement well.Additionally,micro-anchored fiber optic cables have been proven to increase the soil-to-fiber strain transfer efficiency for large deformation monitoring of ground collapse.展开更多
Multicore fiber(MCF)which contains more than one core in a single fiber cladding has attracted ever increasing attention for application in optical sensing systems owing to its unique capability of independent light t...Multicore fiber(MCF)which contains more than one core in a single fiber cladding has attracted ever increasing attention for application in optical sensing systems owing to its unique capability of independent light transmission in multiple spatial channels.Different from the situation in standard single mode fiber(SMF),the fiber bending gives rise to tangential strain in off-center cores,and this unique feature has been employed for directional bending and shape sensing,where strain measurement is achieved by using either fiber Bragg gratings(FBGs),optical frequency-domain reflectometry(OFDR)or Brillouin distributed sensing technique.On the other hand,the parallel spatial cores enable space-division multiplexed(SDM)system configuration that allows for the multiplexing of multiple distributed sensing techniques.As a result,multi-parameter sensing or performance enhanced sensing can be achieved by using MCF.In this paper,we review the research progress in MCF based distributed fiber sensors.Brief introductions of MCF and the multiplexing/de-multiplexing methods are presented.The bending sensitivity of off-center cores is analyzed.Curvature and shape sensing,as well as various SDM distributed sensing using MCF are summarized,and the working principles of diverse MCF sensors are discussed.Finally,we present the challenges and prospects of MCF for distributed sensing applications.展开更多
Railroad condition monitoring is paramount due to frequent passage through densely populated regions.This significance arises from the potential consequences of accidents such as train derailments,hazardous materials ...Railroad condition monitoring is paramount due to frequent passage through densely populated regions.This significance arises from the potential consequences of accidents such as train derailments,hazardous materials leaks,or collisions which may have far-reaching impacts on communities and the surrounding areas.As a solution to this issue,the use of distributed acoustic sensing(DAS)-fiber optic cables along railroads provides a feasible tool for monitoring the health of these extended infrastructures.Nevertheless,analyzing DAS data to assess railroad health or detect potential damage is a challenging task.Due to the large amount of data generated by DAS,as well as the unstructured patterns and substantial noise present,traditional analysis methods are ineffective in interpreting this data.This paper introduces a novel approach that harnesses the power of deep learning through a combination of CNNs and LSTMs,augmented by sliding window techniques(CNN-LSTM-SW),to advance the state-of-the-art in the railroad condition monitoring system.As well as it presents the potential for DAS and fiber optic sensing technologies to revolutionize the proposed CNN-LSTM-SW model to detect conditions along the rail track networks.Extracting insights from the data of High tonnage load(HTL)-a 4.16 km fiber optic and DAS setup,we were able to distinguish train position,normal condition,and abnormal conditions along the railroad.Notably,our investigation demonstrated that the proposed approaches could serve as efficient techniques for processing DAS signals and detecting the condition of railroad infrastructures at any remote distance with DAS-Fiber optic cable setup.Moreover,in terms of pinpointing the train's position,the CNN-LSTM architecture showcased an impressive 97%detection rate.Applying a sliding window,the CNN-LSTM labeled data,the remaining 3%of misclassified labels have been improved dramatically by predicting the exact locations of each type of condition.Altogether,these proposed models exhibit promising potential for accurately identifying various railroad conditions,including anomalies and discrepancies that warrant thorough exploration.展开更多
The long-term settlement of calcareous sand foundations caused by daily periodic fluctuations has become a significant geological hazard,but effective monitoring tools to capture the deformation profiles are still rar...The long-term settlement of calcareous sand foundations caused by daily periodic fluctuations has become a significant geological hazard,but effective monitoring tools to capture the deformation profiles are still rarely reported.In this study,a laboratory model test and an in situ monitoring test were conducted.An optical frequency domain reflectometer(OFDR)with high spatial resolution(1 mm)and high accuracy(10-6)was used to record the soil strain responses to groundwater table and varied loads.The results indicated that the fiber-optic measurements can accurately locate the swelling and compressive zones.During the loading process,the interlock between calcareous sand particles was detected,which increased the internal friction angle of soil.The foundation deformation above the sliding surface was dominated by compression,and the soil was continuously compressed beneath the sliding surface.After 26e48 h,calcareous sand swelling occurred gradually above the water table,which was primarily dependent on capillary water.The swelling of the soil beneath the groundwater table was completed rapidly within less than 2 h.When the groundwater table and load remain constant,the compression creep behavior can be described by the Yasong-Wang model with R2¼0.993.The daily periodically varying in situ deformation of calcareous sand primarily occurs between the highest and lowest groundwater tables,i.e.4.2e6.2 m deep.The tuff interlayers with poor water absorption capacity do not swell or compress,but they produce compressive strain under the influence of deformed calcareous sand layers.展开更多
A recent research campaign at a Canadian nickel-copper mine involved instrumenting a hard rock sill drift pillar with an array of multi-point rod extensometers,distributed optical fibre strain sensors,and borehole pre...A recent research campaign at a Canadian nickel-copper mine involved instrumenting a hard rock sill drift pillar with an array of multi-point rod extensometers,distributed optical fibre strain sensors,and borehole pressure cells(BHPCs).The instrumentation spanned across a 15.24 m lengthwise segment of the relatively massive granitic pillar situated at a depth of 2.44 km within the mine.Between May 2016 and March 2017,the pillar’s displacement and pressure response were measured and correlated with mining activities on the same level as the pillar,including:(1)mine-by of the pillar,(2)footwall drift development,and(3)ore body stoping operations.Regarding displacements of the pillar,the extensometers provided high temporal resolution(logged hourly)and the optical fibre strain sensors provide high spatial resolution(measured every 0.65 mm along the length of each sensor).The combination of sensing techniques allowed centimetre-scale rock mass bulking near the pillar sidewalls to be distinguished from microstrain-scale fracturing towards the core of the pillar.Additionally,the influence and extent of a mine-scale schistose shear zone transecting the pillar was identified.By converting measured rock mass displacement to velocity,a process was demonstrated which allowed mining activities inducing displacements to be categorised by time-duration and cumulative displacement.In over half of the analysed mining activities,displacements were determined to prolong for over an hour,predominately resulting in submillimetre cumulative displacements,but in some cases multi-centimetre cumulative displacements were observed.This time-dependent behaviour was more pronounced within the vicinity of the plumb shear zone.Displacement measurements were also used to assess selected support member load and elongation mobilisation per mining activity.It was found that a combined static load and elongation capacity of reinforcing members was essential to maintaining excavation stability,while permitting gradual shedding of stress through controlled pillar sidewall displacements.展开更多
In cold regions,the widened subgrade could produce uneven frost heave that is detrimental to the pavement.This study investigates the differential frost heave characteristics in a widened subgrade.The field monitoring...In cold regions,the widened subgrade could produce uneven frost heave that is detrimental to the pavement.This study investigates the differential frost heave characteristics in a widened subgrade.The field monitoring system mainly consists of temperature,moisture,and displacement sensors and distributed optical fiber cables for strain measurement.The monitoring results show that the cooling period in the subgrade is longer than the warming period.Water content in the subgrade changes significantly within 0−2 m below the subgrade surface but stabilizes within 2−5 m.The maximum frost heave occurs from February to March.In comparison,the existing subgrade has a longer freezing period and larger heave value,caused by the higher density and water content inside.Water in the existing subgrade migrates into the new one after widening,leading to frost heave reduction in the existing subgrade.Simultaneously,the traffic loads result in the consolidation of the new subgrade,thus reducing the heave value in the second year.In the third year,the water supply from the existing subgrade facilitates the frost heave in the new subgrade.The tensile strain distributions obtained by the distributed optical fiber cables show that the maximum differential frost heave occurs at the joint between the existing and new subgrades.The differential frost heave gradually stabilizes after three years.Finally,an improved frost heave prediction model is developed based on the segregation potential concept and monitoring results.展开更多
Geotechnical engineering is characterized by many uncertainties,including soil material properties,environmental effects,and engineering design and construction,which bring a significant challenge to geotechnical moni...Geotechnical engineering is characterized by many uncertainties,including soil material properties,environmental effects,and engineering design and construction,which bring a significant challenge to geotechnical monitoring.However,conventional sensors with several inherent limitations,such as electromagnetic interference,signal loss in long-distance transmission,and low durability in harsh environments cannot fully meet current monitoring needs.Recently,fiber optic sensing technologies have been successfully applied in geotechnical monitoring due to the significant advantages of anti-electromagnetic interference,stable signal long-distance transmission,high durability,high sensitivity,and lightweight,which can be considered an ideal replacement for conventional sensors.In this paper,the working principle of different fiber optic sensing technologies,the development of fiber optic-based sensors,and the recent application status of these sensing technologies for geotechnical monitoring were comprehensively reviewed and discussed in detail.Finally,the challenges and countermeasures of the sensing technologies in geotechnical monitoring were also presented and discussed.展开更多
Drought-induced desiccation cracking can trigger several weakening mechanisms in surface soils,potentially precipitating instability and failure of slopes and earthen structures.To investigate the potential applicatio...Drought-induced desiccation cracking can trigger several weakening mechanisms in surface soils,potentially precipitating instability and failure of slopes and earthen structures.To investigate the potential application of distributed fibre optical sensing(DFOS)based on optical frequency domain reflectometry(OFDR)technology in characterizing the twodimensional(2D)desiccation cracking processes of surface soils,a comprehensive test device is utilized to conduct soil evaporation tests,continuously record water content changes,desiccation cracking evolution,and FO sensing strain status.A deep learning-based quantitative analysis method is employed to meticulously examine the relationship between 2D cracking geometric parameters and strain status.The comprehensive analysis not only reveals the mutual feedback response mechanism between the strain status and the soil evaporation-shrinkage-cracking processes,but also clarifies the early detection distance of OFDR technology for 2D desiccation cracking.Specifically,OFDR technology can detect the propagation of horizontal desiccation cracks up to 23 mm in advance with a strain measurement accuracy of 1με.To address the spatial continuity issue in OFDR sensing strain data,an innovative high-resolution characterization framework is proposed by combining the finite element method(FEM)and OFDR technology,referred to as the FEM-OFDR framework.Comparative results indicate that the proposed FEM significantly surpasses both the kriging and radial basis function(RBF)methods in inferring missing OFDR sensing strain data.Notably,during the drying process,reaching a critical water content causes the local decoupling between the uncracked clods and the substrate,resulting in a decreasing trend in the sensing strain at the crack position.This study provides crucial technical means and theoretical support for a deeper understanding of the mechanisms driving 2D desiccation-induced shrinkage and cracking in surface soils.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.U23A20375 and 62075151)the National Key Research and Development Program of China(Grant No.202103021223042).
文摘The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system with kilometer-level sensing distance and submeter spatial resolution.Based on this,we propose a Raman distributed optical fiber sensing scheme based on chaotic pulse cluster demodulation.Chaotic pulse clusters are used as the probe signal,in preference to conventional pulsed or chaotic single-pulse lasers.Furthermore,the accurate positioning of the temperature variety region along the sensing fiber can be realized using chaotic pulse clusters.The proposed demodulation scheme can enhance the signal-to-noise ratio by improving the correlation between the chaotic reference and the chaotic Raman anti-Stokes scattering signals.The experiment achieved a sensing spatial resolution of 30 cm at a distributed temperature-sensing distance of∼6.0 km.Furthermore,we explored the influence of chaotic pulse width and detector bandwidth on the sensing spatial resolution.In addition,the theoretical experiments proved that the sensing spatial resolution in the proposed scheme was independent of the pulse width and sensing distance.
基金support from the Open Research Project Programme of the State Key Laboratory of Internet of Things for Smart City,University of Macao (Grant No.SKL-IoTSC (UM)-2021-2023/ORPF/A19/2022)the General Research Fund project from Research Grants Council of Hong Kong Special Administrative Region Government of China (Grant No.15214722)the Start-up Fund from The Hong Kong Polytechnic University (Grant No.BD88).
文摘Despite the extensive use of distributed fiber optic sensing(DFOS)in monitoring underground structures,its potential in detecting structural anomalies,such as cracks and cavities,is still not fully understood.To contribute to the identification of defects in underground structures,this study conducted a four-point bending test of a reinforced concrete(RC)beam and uniaxial loading tests of an RC specimen with local cavities.The experimental results revealed the disparity in DFOS strain spike profiles between these two structural anomalies.The effectiveness of DFOS in the quantification of crack opening displacement(COD)was also demonstrated,even in cases where perfect bonding was not achievable between the cable and structures.In addition,DFOS strain spikes observed in two diaphragm wall panels of a twin circular shaft were also reported.The most probable cause of those spikes was identified as the mechanical behavior associated with local concrete contamination.With the utilization of the strain profiles obtained from laboratory tests and field monitoring,three types of multi-classifiers,based on support vector machine(SVM),random forest(RF),and backpropagation neural network(BP),were employed to classify strain profiles,including crack-induced spikes,non-crack-induced spikes,and non-spike strain profiles.Among these classifiers,the SVM-based classifier exhibited superior performance in terms of accuracy and model robustness.This finding suggests that the SVM-based classifier holds promise as a potential solution for the automatic detection and classification of defects in underground structures during long-term monitoring.
基金support provided by Science Foundation Ireland Frontiers for the Future Programme,21/FFP-P/10090.
文摘Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their service life is essential for the overall functionality of geotechnical infrastructure.Distributed Brillouin sensing(DBS)is increasingly applied in geotechnical projects due to its ability to acquire spatially continuous strain and temperature distributions over distances of up to 150 km using a single optical fibre.However,limited by the complex operations of distributed optic fibre sensing(DFOS)sensors in curved structures,previous reports about exploiting DBS in geotechnical structural health monitoring(SHM)have mostly been focused on flat surfaces.The lack of suitable DFOS installation methods matched to the spatial characteristics of continuous monitoring is one of the major factors that hinder the further application of this technique in curved structures.This review paper starts with a brief introduction of the fundamental working principle of DBS and the inherent limitations of DBS being used on monitoring curved surfaces.Subsequently,the state-of-the-art installation methods of optical fibres in curved structures are reviewed and compared to address the most suitable scenario of each method and their advantages and disadvantages.The installation challenges of optical fibres that can highly affect measurement accuracy are also discussed in the paper.
基金Supported by Key Laboratory of Space Active Optical-Electro Technology of Chinese Academy of Sciences(2021ZDKF4)。
文摘Phase-sensitive Optical Time-Domain Reflectometer(φ-OTDR)technology facilitates the real-time detection of vibration events along fiber optic cables by analyzing changes in Rayleigh scattering signals.This technology is widely used in applications such as intrusion monitoring and structural health assessments.Traditional signal processing methods,such as Support Vector Machines(SVM)and K-Nearest Neighbors(KNN),have limitations in feature extraction and classification in complex environments.Conversely,a single deep learning model often struggles with capturing long time-series dependencies and mitigating noise interference.In this study,we propose a deep learning model that integrates Convolutional Neural Network(CNN),Long Short-Term Memory Network(LSTM),and Transformer modules,leveraging φ-OTDR technology for distributed fiber vibration sensing event recognition.The hybrid model combines the CNN's capability to extract local features,the LSTM's ability to model temporal dynamics,and the Transformer's proficiency in capturing global dependencies.This integration significantly enhances the accuracy and robustness of event recognition.In experiments involving six types of vibration events,the model consistently achieved a validation accuracy of 0.92,and maintained a validation loss of approximately 0.2,surpassing other models,such as TAM+BiLSTM and CNN+CBAM.The results indicate that the CNN+LSTM+Transformer model is highly effective in handling vibration signal classification tasks in complex scenarios,offering a promising new direction for the application of fiber optic vibration sensing technology.
基金supported by the 34th Research Institute of CETC Funding(Grant No.K134002021S604)the New Technology Research University Cooperation Project of the 34th Research Institute of CETC(Grant No.2021-1200-05-001900).
文摘Presented here is long-range distributed vibration sensing based on internal-modulation optical frequency domain reflectometry(OFDR).In the proposed system with internal modulation,a silicon-based photonic-chip laser is used as the laser source,and by controlling the output voltage curve of an arbitrary waveform generator to induce temperature change in the external cavity of the laser,a 10-GHz optical frequency tuning range is achieved.The complexity of the proposed internal-modulation system is lower than that of the traditional external-modulation OFDR system that combines a narrow-linewidth laser with a single-sideband modulator to achieve wavelength tuning.Cross-correlation analysis is used as a sensing mechanism to evaluate the similarity between Rayleigh scatter signals and to achieve vibration event localization.Experimental comparison is made of the vibration sensing performance of the external-and internal-modulation systems,and for a vibration event generated at a distance of 100.95 km,they locate it with a sensing spatial resolution of 43.0 m and 16.8 m,respectively.The results indicates that the proposed distributed vibration sensing based on internal modulation has better sensing performance and lower complexity compared to the traditional external-modulation system.In addition,the proposed system is single-ended and involves no optical amplification,which makes it very suitable for ultra-long-range sensing.
基金Supported by the Scientific Research and Technology Development Project of Petrochina Southwest Oil and Gas Field Company(20230307-02)。
文摘The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibration signals induced by external events and to effectively provide early warnings of potential intrusion activities.Due to the complexity and diversity of external intrusion events,traditional deep learning methods can achieve event recognition with an average accuracy exceeding 90%.However,these methods rely on large-scale datasets,leading to significant time and labor costs during the data collection process.Additionally,traditional methods perform poorly when faced with the scarcity of low-frequency event samples,making it challenging to address these rare occurrences.To address this issue,this paper proposes a small-sample learning model based on triplet learning for intrusion event recognition.The model employs a 6-way 20-shot support set configuration and utilizes the KNN clustering algorithm to assess the model's performance.Experimental results indicate that the model achieves an average accuracy of 91.6%,further validating the superior performance of the triplet learning model in classifying external intrusion events.Compared to traditional methods,this approach not only effectively reduces the dependence on large-scale datasets but also better addresses the classification of low-frequency event samples,demonstrating significant application potential.
基金support from the Institute of Crustal Dynamics,China Earthquake Administration(Grant No.ZDJ2016-20 and ZDJ2019-15)。
文摘This paper investigates the deformation and fracture propagation of sandstone specimen under uniaxial compression using the distributed fiber optic strain sensing(DFOSS)technology.It shows that the DFOSS-based circumferential strains are in agreement with the data monitored with the traditional strain gage.The DFOSS successfully scans the full-field view of axial and circumferential strains on the specimen surface.The spatiotemporal strain measurement based on DFOSS manifests crack closure and elastoplastic deformation,detects initialization of microcrack nucleation,and identifies strain localization within the specimen.The DFOSS well observes the effects of rock heterogeneity on rock deformation.The advantage of DFOSS-based strain acquisition includes the high spatiotemporal resolution of signals and the ability of full-surface strain scanning.The introduction to the DFOSS technology yields a better understanding of the rock damage process under uniaxial compression.
基金funding support from the Israeli Ministry of Housing and Construction(Grant No.2028286).
文摘Confinement of rock bolts by the surrounding rock formation has long been recognized as a positive contributor to the pull-out behavior,yet only a few experimental works and analytical models have been reported,most of which are based on the global rock bolt response evaluated in pull-out tests.This paper presents a laboratory experimental setup aiming to capture the rock formation effect,while using distributed fiber optic sensing to quantify the effect of the confinement and the reinforcement pull-out behavior on a more local level.It is shown that the behavior along the sample itself varies,with certain points exhibiting stress drops with crack formation.Some edge effects related to the kinematic freedom of the grout to dilate are also observed.Regardless,it was found that the mid-level response is quite similar to the average response along the sample.The ability to characterize the variation of the response along the sample is one of the many advantages high-resolution fiber optic sensing allows in such investigations.The paper also offers a plasticity-based hardening load transfer function,representing a"slice"of the anchor.The paper describes in detail the development of the model and the calibration/determination of its parameters.The suggested model captures well the coupled behavior in which the pull-out process leads to an increase in the confining stress due to dilative behavior.
基金supported in part by the National Natural Science Foundation of China(Grant No.U22A20206)the Key Research and Development Plan Project of Hubei Province,China(Grant No.2022BAA004)Zhejiang Provincial Market Supervision Bureau Young Eagle Plan Project,China(Grant No.CY2022228).
文摘We have numerically and experimentally investigated the flow rate measurement of the pipeline based on the optical fiber.Employing the large eddy simulation(LES)model,we have quantitatively analyzed the pressure fluctuation of the pipe wall caused by the turbulent flow in the pipeline.The simulation results have shown that the standard deviation of pressure fluctuation was quadratic with the flow rate.We have verified the theoretical model by using a distributed optical fiber acoustic sensing(DAS)system in the flow rate range from 0.61 m/s to 2.42 m/s.The experimental results were consistent with the simulation results very well.Furthermore,to improve the measuring error at the low flow rate,we have employed the composite adaptive denoising algorithm to eliminate the background noise and system noise.The final results have shown that the minimum goodness of fit was improved from 0.962 to 0.997,and the variation of the quadratic coefficient significantly decreased by 93.25%.The measured flow rate difference was only 0.84%between different sensing points in repeated experiments.
基金the funding support from Alpha Foundation for the Improvement of Mine Safety and Health Inc.(ALPHAFOUNDATION,Grant No.AFC820-52)。
文摘Underground mine pillars provide natural stability to the mine area,allowing safe operations for workers and machinery.Extensive prior research has been conducted to understand pillar failure mechanics and design safe pillar layouts.However,limited studies(mostly based on empirical field observation and small-scale laboratory tests)have considered pillar-support interactions under monotonic loading conditions for the design of pillar-support systems.This study used a series of large-scale laboratory compression tests on porous limestone blocks to analyze rock and support behavior at a sufficiently large scale(specimens with edge length of 0.5 m)for incorporation of actual support elements,with consideration of different w/h ratios.Both unsupported and supported(grouted rebar rockbolt and wire mesh)tests were conducted,and the surface deformations of the specimens were monitored using three-dimensional(3D)digital image correlation(DIC).Rockbolts instrumented with distributed fiber optic strain sensors were used to study rockbolt strain distribution,load mobilization,and localized deformation at different w/h ratios.Both axial and bending strains were observed in the rockbolts,which became more prominent in the post-peak region of the stress-strain curve.
基金supported by Universita della Campania“L.Vanvitelli”,Program VALERE“VAnviteLli pEr la RicErca”(Grant No.516/2018)Italian Ministry of Economic Development#NOACRONYM Project,PoC MISE 2021.
文摘Extensive urban areas worldwide face significant landslide hazards, impacting inhabitants, buildings, and critical infrastructures alike. In the case of slow-moving deep-seated landslides involving huge areas and characterized by complex patterns, when the cost of repairing infrastructures, relocating communities, and restoring cultural sites might be such that it is unsustainable for the community, the exposed structures require significant effort for their surveillance and protection, which can be supported by the development of innovative monitoring systems. For this purpose, a smart extenso-inclinometer, realized by equipping a conventional inclinometer tube with distributed strain and temperature transducers based on optical fiber sensing technology, is presented. In situ monitoring of the active deep-seated San Nicola landslide in Centola (Campania, southern Italy) demonstrated its ability to capture the main features of movements and reconstruct a tridimensional evolution of the landslide pattern, even when the entity of both vertical and horizontal soil strain components is comparable. Although further tests are needed to definitively ascertain the extensometer function of the new device, by interpreting the strain profiles of the landslide body and identifying the achievement of predetermined thresholds, this system could provide a warning of the trigger of a landslide event. The use of the smart extenso-inclinometer within an early warning system for slow-moving landslides holds immense potential for reducing the impact of landslide events.
基金funding support from the National Natural Science Foundation of China (Grant No. 42225702)the Central Government Guided Local Science and Technology Development Fund (Grant No. 226Z5404G)the Natural Science Foundation of Hebei Province,China (Grant No. D2022508002)。
文摘Understanding the spatiotemporal evolution of overburden deformation during coal mining is still a challenge in engineering practice due to the limitation of monitoring techniques. Taking the Yangliu Coal Mine as an example, a similarity model test was designed and conducted to investigate the deformation and failure mechanism of overlying rocks in this study. Distributed fiber optic sensing(DFOS), highdensity electrical resistivity tomography(HD-ERT) and close-range photogrammetry(CRP) technologies were used in the test for comprehensive analyses. The combined use of the three methods facilitates the investigation of the spatiotemporal evolution characteristics of overburden deformation, showing that the mining-induced deformation of overburden strata was a dynamic evolution process. This process was accompanied by the formation, propagation, closure and redevelopment of separation cracks.Moreover, the key rock stratum with high strength and high-quality lithology played a crucial role in the whole process of overburden deformation. There were generally three failure modes of overburden rock layers, including bending and tension, overall shearing, and shearing and sliding. Shear failure often leads to overburden falling off in blocks, which poses a serious threat to mining safety. Therefore, realtime and accurate monitoring of overburden deformation is of great significance for the safe mining of underground coal seams.
基金support provided by the National Natural Science Foundation of China(Grant Nos.42225702,and 42077232)the Open Research Project Program of the State Key Laboratory of Internet of Things for Smart City(University of Macao)(Grant No.SKL-IoTSC(UM)-2021-2023/ORP/GA10/2022).
文摘Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This paper presents an experimental study to evaluate the feasibility of fiber optic strain sensing nerves in sinkhole monitoring.Combining the artificial neural network(ANN)and particle image velocimetry(PIV)techniques,a series of model tests have been performed to explore the relationship between strain measurements and sinkhole development and to establish a conversion model from strain data to ground settlements.It is demonstrated that the failure mechanism of the soil above the sinkhole developed from a triangle failure plane to a vertical failure plane with increasing collapse volume.Meanwhile,the soil-embedded fiber optic strain sensing nerves allowed deformation monitoring of the ground soil in real time.Furthermore,the characteristics of the measured strain profiles indicate the locations of sinkholes and the associated shear bands.Based on the strain data,the ANN model predicts the ground settlement well.Additionally,micro-anchored fiber optic cables have been proven to increase the soil-to-fiber strain transfer efficiency for large deformation monitoring of ground collapse.
文摘Multicore fiber(MCF)which contains more than one core in a single fiber cladding has attracted ever increasing attention for application in optical sensing systems owing to its unique capability of independent light transmission in multiple spatial channels.Different from the situation in standard single mode fiber(SMF),the fiber bending gives rise to tangential strain in off-center cores,and this unique feature has been employed for directional bending and shape sensing,where strain measurement is achieved by using either fiber Bragg gratings(FBGs),optical frequency-domain reflectometry(OFDR)or Brillouin distributed sensing technique.On the other hand,the parallel spatial cores enable space-division multiplexed(SDM)system configuration that allows for the multiplexing of multiple distributed sensing techniques.As a result,multi-parameter sensing or performance enhanced sensing can be achieved by using MCF.In this paper,we review the research progress in MCF based distributed fiber sensors.Brief introductions of MCF and the multiplexing/de-multiplexing methods are presented.The bending sensitivity of off-center cores is analyzed.Curvature and shape sensing,as well as various SDM distributed sensing using MCF are summarized,and the working principles of diverse MCF sensors are discussed.Finally,we present the challenges and prospects of MCF for distributed sensing applications.
基金supported by funding from The Association of American Railroads(AAR)-MxV Rail(Award number:21-0825-007538)Impact Area Accelerator Award Grant 2023 from Georgia Southern University's Office of Research.
文摘Railroad condition monitoring is paramount due to frequent passage through densely populated regions.This significance arises from the potential consequences of accidents such as train derailments,hazardous materials leaks,or collisions which may have far-reaching impacts on communities and the surrounding areas.As a solution to this issue,the use of distributed acoustic sensing(DAS)-fiber optic cables along railroads provides a feasible tool for monitoring the health of these extended infrastructures.Nevertheless,analyzing DAS data to assess railroad health or detect potential damage is a challenging task.Due to the large amount of data generated by DAS,as well as the unstructured patterns and substantial noise present,traditional analysis methods are ineffective in interpreting this data.This paper introduces a novel approach that harnesses the power of deep learning through a combination of CNNs and LSTMs,augmented by sliding window techniques(CNN-LSTM-SW),to advance the state-of-the-art in the railroad condition monitoring system.As well as it presents the potential for DAS and fiber optic sensing technologies to revolutionize the proposed CNN-LSTM-SW model to detect conditions along the rail track networks.Extracting insights from the data of High tonnage load(HTL)-a 4.16 km fiber optic and DAS setup,we were able to distinguish train position,normal condition,and abnormal conditions along the railroad.Notably,our investigation demonstrated that the proposed approaches could serve as efficient techniques for processing DAS signals and detecting the condition of railroad infrastructures at any remote distance with DAS-Fiber optic cable setup.Moreover,in terms of pinpointing the train's position,the CNN-LSTM architecture showcased an impressive 97%detection rate.Applying a sliding window,the CNN-LSTM labeled data,the remaining 3%of misclassified labels have been improved dramatically by predicting the exact locations of each type of condition.Altogether,these proposed models exhibit promising potential for accurately identifying various railroad conditions,including anomalies and discrepancies that warrant thorough exploration.
基金support provided by the National Natural Science Foundation of China(Grant No.41907244)China Postdoctoral Science Foundation(Grant No.2019M653180)the Project of the Key Laboratory of Soft Soil and Environmental Geotechnical Ministry of Education(Grant No.2019P05)is gratefully acknowledged.
文摘The long-term settlement of calcareous sand foundations caused by daily periodic fluctuations has become a significant geological hazard,but effective monitoring tools to capture the deformation profiles are still rarely reported.In this study,a laboratory model test and an in situ monitoring test were conducted.An optical frequency domain reflectometer(OFDR)with high spatial resolution(1 mm)and high accuracy(10-6)was used to record the soil strain responses to groundwater table and varied loads.The results indicated that the fiber-optic measurements can accurately locate the swelling and compressive zones.During the loading process,the interlock between calcareous sand particles was detected,which increased the internal friction angle of soil.The foundation deformation above the sliding surface was dominated by compression,and the soil was continuously compressed beneath the sliding surface.After 26e48 h,calcareous sand swelling occurred gradually above the water table,which was primarily dependent on capillary water.The swelling of the soil beneath the groundwater table was completed rapidly within less than 2 h.When the groundwater table and load remain constant,the compression creep behavior can be described by the Yasong-Wang model with R2¼0.993.The daily periodically varying in situ deformation of calcareous sand primarily occurs between the highest and lowest groundwater tables,i.e.4.2e6.2 m deep.The tuff interlayers with poor water absorption capacity do not swell or compress,but they produce compressive strain under the influence of deformed calcareous sand layers.
文摘A recent research campaign at a Canadian nickel-copper mine involved instrumenting a hard rock sill drift pillar with an array of multi-point rod extensometers,distributed optical fibre strain sensors,and borehole pressure cells(BHPCs).The instrumentation spanned across a 15.24 m lengthwise segment of the relatively massive granitic pillar situated at a depth of 2.44 km within the mine.Between May 2016 and March 2017,the pillar’s displacement and pressure response were measured and correlated with mining activities on the same level as the pillar,including:(1)mine-by of the pillar,(2)footwall drift development,and(3)ore body stoping operations.Regarding displacements of the pillar,the extensometers provided high temporal resolution(logged hourly)and the optical fibre strain sensors provide high spatial resolution(measured every 0.65 mm along the length of each sensor).The combination of sensing techniques allowed centimetre-scale rock mass bulking near the pillar sidewalls to be distinguished from microstrain-scale fracturing towards the core of the pillar.Additionally,the influence and extent of a mine-scale schistose shear zone transecting the pillar was identified.By converting measured rock mass displacement to velocity,a process was demonstrated which allowed mining activities inducing displacements to be categorised by time-duration and cumulative displacement.In over half of the analysed mining activities,displacements were determined to prolong for over an hour,predominately resulting in submillimetre cumulative displacements,but in some cases multi-centimetre cumulative displacements were observed.This time-dependent behaviour was more pronounced within the vicinity of the plumb shear zone.Displacement measurements were also used to assess selected support member load and elongation mobilisation per mining activity.It was found that a combined static load and elongation capacity of reinforcing members was essential to maintaining excavation stability,while permitting gradual shedding of stress through controlled pillar sidewall displacements.
基金supported by the National Natural Science Foundation of China(Nos.42171128,41971076)the National Key Research and Development Program of China(No.2018YFC1505306)the Key Research and Development Program of Heilongjiang Province(No.GA21A501).
文摘In cold regions,the widened subgrade could produce uneven frost heave that is detrimental to the pavement.This study investigates the differential frost heave characteristics in a widened subgrade.The field monitoring system mainly consists of temperature,moisture,and displacement sensors and distributed optical fiber cables for strain measurement.The monitoring results show that the cooling period in the subgrade is longer than the warming period.Water content in the subgrade changes significantly within 0−2 m below the subgrade surface but stabilizes within 2−5 m.The maximum frost heave occurs from February to March.In comparison,the existing subgrade has a longer freezing period and larger heave value,caused by the higher density and water content inside.Water in the existing subgrade migrates into the new one after widening,leading to frost heave reduction in the existing subgrade.Simultaneously,the traffic loads result in the consolidation of the new subgrade,thus reducing the heave value in the second year.In the third year,the water supply from the existing subgrade facilitates the frost heave in the new subgrade.The tensile strain distributions obtained by the distributed optical fiber cables show that the maximum differential frost heave occurs at the joint between the existing and new subgrades.The differential frost heave gradually stabilizes after three years.Finally,an improved frost heave prediction model is developed based on the segregation potential concept and monitoring results.
基金funded by the National Natural Science Foundation of China(grant no.52122805,52078103,42225702).
文摘Geotechnical engineering is characterized by many uncertainties,including soil material properties,environmental effects,and engineering design and construction,which bring a significant challenge to geotechnical monitoring.However,conventional sensors with several inherent limitations,such as electromagnetic interference,signal loss in long-distance transmission,and low durability in harsh environments cannot fully meet current monitoring needs.Recently,fiber optic sensing technologies have been successfully applied in geotechnical monitoring due to the significant advantages of anti-electromagnetic interference,stable signal long-distance transmission,high durability,high sensitivity,and lightweight,which can be considered an ideal replacement for conventional sensors.In this paper,the working principle of different fiber optic sensing technologies,the development of fiber optic-based sensors,and the recent application status of these sensing technologies for geotechnical monitoring were comprehensively reviewed and discussed in detail.Finally,the challenges and countermeasures of the sensing technologies in geotechnical monitoring were also presented and discussed.
基金supported by the National Natural Science Foundation of China(Grant Nos.41925012,42230710,42172290)the Natural Science Foundation of Jiangsu Province(Grant No.BK20211087)+2 种基金the Key Laboratory Cooperation Special Project of Western Cross Team of Western Light,CAS(Grant No.xbzg-zdsys-202107)the China Scholarship Council(Grant No.202206190069)the Fundamental Research Funds for the Central Universities。
文摘Drought-induced desiccation cracking can trigger several weakening mechanisms in surface soils,potentially precipitating instability and failure of slopes and earthen structures.To investigate the potential application of distributed fibre optical sensing(DFOS)based on optical frequency domain reflectometry(OFDR)technology in characterizing the twodimensional(2D)desiccation cracking processes of surface soils,a comprehensive test device is utilized to conduct soil evaporation tests,continuously record water content changes,desiccation cracking evolution,and FO sensing strain status.A deep learning-based quantitative analysis method is employed to meticulously examine the relationship between 2D cracking geometric parameters and strain status.The comprehensive analysis not only reveals the mutual feedback response mechanism between the strain status and the soil evaporation-shrinkage-cracking processes,but also clarifies the early detection distance of OFDR technology for 2D desiccation cracking.Specifically,OFDR technology can detect the propagation of horizontal desiccation cracks up to 23 mm in advance with a strain measurement accuracy of 1με.To address the spatial continuity issue in OFDR sensing strain data,an innovative high-resolution characterization framework is proposed by combining the finite element method(FEM)and OFDR technology,referred to as the FEM-OFDR framework.Comparative results indicate that the proposed FEM significantly surpasses both the kriging and radial basis function(RBF)methods in inferring missing OFDR sensing strain data.Notably,during the drying process,reaching a critical water content causes the local decoupling between the uncracked clods and the substrate,resulting in a decreasing trend in the sensing strain at the crack position.This study provides crucial technical means and theoretical support for a deeper understanding of the mechanisms driving 2D desiccation-induced shrinkage and cracking in surface soils.
