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
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
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
At present, the demand for perimeter security system is in-creasing greatly, especially for such system based on distribut-ed optical fiber sensing. This paper proposes a perimeter se-curity monitoring system based on...At present, the demand for perimeter security system is in-creasing greatly, especially for such system based on distribut-ed optical fiber sensing. This paper proposes a perimeter se-curity monitoring system based on phase-sensitive coherentoptical time domain reflectometry(Ф-COTDR) with the practi-cal pattern recognition function. We use fast Fourier trans-form(FFT) to exact features from intrusion events and a multi-class classification algorithm derived from support vector ma-chine(SVM) to work as a pattern recognition technique. Fivedifferent types of events are classified by using a classifica-tion algorithm based on SVM through a three-dimensional fea-ture vector. Moreover, the identification results of the patternrecognition system show that an identification accurate rate of92.62% on average can be achieved.展开更多
We demonstrate a distributed two-dimensional(2D)strain-sensing system in optical frequency domain reflectometry(OFDR)with an Archimedean spiral arrangement of the sensing fiber.The Archimedean spiral describes a simpl...We demonstrate a distributed two-dimensional(2D)strain-sensing system in optical frequency domain reflectometry(OFDR)with an Archimedean spiral arrangement of the sensing fiber.The Archimedean spiral describes a simple relationship between the radial radius and polar angle,such that each circle(the polar angle from0 to 2π)can sense the 2D strain in all directions.The strain between two adjacent circles can also be easily obtained because an Archimedean spiral facilitates sensing of every angle covering the full 2D range.Based on the mathematical relation of Archimedean spirals,we deduce the relationship between the one-dimensional position of the sensing fiber and 2D distribution in polar coordinates.The results of the experiment show that an Archimedean spiral arrangement system can achieve 2D strain sensing with different strain load angles.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
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
In the discipline of geotechnical engineering, fiber optic sensor based distributed monitoring has played an increasingly important role over the past few decades. Compared with conventional sensors, fiber optic senso...In the discipline of geotechnical engineering, fiber optic sensor based distributed monitoring has played an increasingly important role over the past few decades. Compared with conventional sensors, fiber optic sensors have a variety of exclusive advantages, such as smaller size, higher precision, and better corrosion resistance. These innovative monitoring technologies have been successfully applied for performance monitoring of geo-structures and early warning of potential geo- hazards around the world. In order to investigate their ability to monitor slope stability problems, a medium-sized model of soil nailed slope has been constructed in laboratory. The fully distributed Brillouin optical time-domain analysis （BOTDA） sensing technology was employed to measure the horizontal strain distributions inside the model slope. During model construction, a specially designed strain sensing fiber was buried in the soil mass. Afterward, the surcharge loading was applied on the slope crest in stages using hydraulic jacks and a reaction frame. During testing, an NBX-6o5o BOTDA sensing interrogator was used to collect the fiber optic sensing data. The test results have been analyzed in detail, which shows that the fiber optic sensors can capture the progressive deformation and failure pattern of the model slope. The limit equilibrium analyses were also conducted to obtain the factors ofsafety of the slope under different surface loadings. It is found that the characteristic maximum strains can reflect the stability of the model slope and an empirical relationship was obtained, This study verified the effectiveness of the distributed BOTDA sensing technology in performance monitoring of slope.展开更多
Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study pr...Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover tunnels.DFOS systems based on Brillouin and Rayleigh scattering principles are both considered.When implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining surface.There are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor instrumentation.These four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.展开更多
Moisture content is a fundamental physical index that quantifies soil property and is closely associatedwith the hydrological, ecological and engineering behaviors of soil. To measure in-situ soil moisturecontents, a ...Moisture content is a fundamental physical index that quantifies soil property and is closely associatedwith the hydrological, ecological and engineering behaviors of soil. To measure in-situ soil moisturecontents, a distributed measurement system for in-situ soil moisture content （SM-DTS） is introduced.The system is based on carbon-fiber heated cable （CFHC） technology that has been developed to enhancethe measuring accuracy of in-situ soil moisture content. Using CFHC technique, a temperature characteristicvalue （Tt） can be defined from temperatureetime curves. A relationship among Tt, soil thermalimpedance coefficient and soil moisture content is then established in laboratory. The feasibility of theSM-DTS technology to provide distributed measurements of in-situ soil moisture content is verifiedthrough field tests. The research reported herein indicates that the proposed SM-DTS is capable ofmeasuring in-situ soil moisture content over long distances and large areas.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
Based on advantages of technology of distributive fiber-optic temperature sensing and specific to its applications in monitoring mine conflagration, the corresponding Processes such as connection arrangement, signal t...Based on advantages of technology of distributive fiber-optic temperature sensing and specific to its applications in monitoring mine conflagration, the corresponding Processes such as connection arrangement, signal transmission and monitoring were illustrated. As applied in Sitai Coal Mine of Datong Coal Mine Group Co., this method is effective and accurate and could provide reliable gist for monitoring spontaneous combustion in gob area of mines.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
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
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.
文摘At present, the demand for perimeter security system is in-creasing greatly, especially for such system based on distribut-ed optical fiber sensing. This paper proposes a perimeter se-curity monitoring system based on phase-sensitive coherentoptical time domain reflectometry(Ф-COTDR) with the practi-cal pattern recognition function. We use fast Fourier trans-form(FFT) to exact features from intrusion events and a multi-class classification algorithm derived from support vector ma-chine(SVM) to work as a pattern recognition technique. Fivedifferent types of events are classified by using a classifica-tion algorithm based on SVM through a three-dimensional fea-ture vector. Moreover, the identification results of the patternrecognition system show that an identification accurate rate of92.62% on average can be achieved.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.61505138,61635008,61475114,61735011)in part by the Tianjin Science and Technology Support Plan Program Funding(Grant No.16JCQNJC01800)+2 种基金in part by the China Postdoctoral Science Foundation(Grant Nos.2015M580199,2016T90205)in part by the National Instrumentation Program(Grant No.2013YQ030915)in part by the National Key Research and Development Program(Grant No.2016YFC0100500)
文摘We demonstrate a distributed two-dimensional(2D)strain-sensing system in optical frequency domain reflectometry(OFDR)with an Archimedean spiral arrangement of the sensing fiber.The Archimedean spiral describes a simple relationship between the radial radius and polar angle,such that each circle(the polar angle from0 to 2π)can sense the 2D strain in all directions.The strain between two adjacent circles can also be easily obtained because an Archimedean spiral facilitates sensing of every angle covering the full 2D range.Based on the mathematical relation of Archimedean spirals,we deduce the relationship between the one-dimensional position of the sensing fiber and 2D distribution in polar coordinates.The results of the experiment show that an Archimedean spiral arrangement system can achieve 2D strain sensing with different strain load angles.
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 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.
基金the financial support provided by the National Basic Research Program of China (973 Program) (Grant No. 2011CB710605)the National Natural Science Foundation of China (Grant Nos. 41102174, 41302217)supported by the National Key Technology R&D Program of China (Grant No. 2012BAK10B05)
文摘In the discipline of geotechnical engineering, fiber optic sensor based distributed monitoring has played an increasingly important role over the past few decades. Compared with conventional sensors, fiber optic sensors have a variety of exclusive advantages, such as smaller size, higher precision, and better corrosion resistance. These innovative monitoring technologies have been successfully applied for performance monitoring of geo-structures and early warning of potential geo- hazards around the world. In order to investigate their ability to monitor slope stability problems, a medium-sized model of soil nailed slope has been constructed in laboratory. The fully distributed Brillouin optical time-domain analysis （BOTDA） sensing technology was employed to measure the horizontal strain distributions inside the model slope. During model construction, a specially designed strain sensing fiber was buried in the soil mass. Afterward, the surcharge loading was applied on the slope crest in stages using hydraulic jacks and a reaction frame. During testing, an NBX-6o5o BOTDA sensing interrogator was used to collect the fiber optic sensing data. The test results have been analyzed in detail, which shows that the fiber optic sensors can capture the progressive deformation and failure pattern of the model slope. The limit equilibrium analyses were also conducted to obtain the factors ofsafety of the slope under different surface loadings. It is found that the characteristic maximum strains can reflect the stability of the model slope and an empirical relationship was obtained, This study verified the effectiveness of the distributed BOTDA sensing technology in performance monitoring of slope.
基金funding support from Rijkswaterstaat,the Netherlands,and European Union’s Horizon 2020 Research and Innovation Programme(Project SAFE-10-T under Grant No.723254)China Scholarship Council,and National Natural Science Foundation of China(Grant No.42225702).
文摘Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover tunnels.DFOS systems based on Brillouin and Rayleigh scattering principles are both considered.When implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining surface.There are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor instrumentation.These four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.
基金The financial supports provided by the National Natural Science Foundation of China(Grant Nos.41230636,41372265,41427801)National Basic Research Program of China(973 Project)(Grant No.2011CB710605)
文摘Moisture content is a fundamental physical index that quantifies soil property and is closely associatedwith the hydrological, ecological and engineering behaviors of soil. To measure in-situ soil moisturecontents, a distributed measurement system for in-situ soil moisture content （SM-DTS） is introduced.The system is based on carbon-fiber heated cable （CFHC） technology that has been developed to enhancethe measuring accuracy of in-situ soil moisture content. Using CFHC technique, a temperature characteristicvalue （Tt） can be defined from temperatureetime curves. A relationship among Tt, soil thermalimpedance coefficient and soil moisture content is then established in laboratory. The feasibility of theSM-DTS technology to provide distributed measurements of in-situ soil moisture content is verifiedthrough field tests. The research reported herein indicates that the proposed SM-DTS is capable ofmeasuring in-situ soil moisture content over long distances and large areas.
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 the National Natural Science Foundation of China （50375026,50375028）
文摘Based on advantages of technology of distributive fiber-optic temperature sensing and specific to its applications in monitoring mine conflagration, the corresponding Processes such as connection arrangement, signal transmission and monitoring were illustrated. As applied in Sitai Coal Mine of Datong Coal Mine Group Co., this method is effective and accurate and could provide reliable gist for monitoring spontaneous combustion in gob area of mines.
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 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.
