Brillouin fiber optic sensors and mobile augmented reality-based digital twins for quantitative safety assessment of underground pipelines

Li, Minghao; Feng, Xin; Han, Yang

doi:10.1016/j.autcon.2022.104617

Cited by 42 publications

(4 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When incidents such as third-party construction events, manual mechanical excavation events, natural disaster damage, or oil and gas theft occur, coherent optical time domain reflectometry (COTDR) can be used to analyze the distribution characteristics in different monitoring environments. This allows for the identification of alarm types and accurate localization of the incident location. , According to the frequency of abnormal distribution observed in the COTDR data within a month, this study classified the warning levels for each segment of the fiber optic system. The higher the frequency of abnormalities, the more frequent the occurrence of third-party damage activities during that period, resulting in a higher warning level.…”

Section: Case Studymentioning

confidence: 99%

“…This allows for the identification of alarm types and accurate localization of the incident location. 52 , 53 According to the frequency of abnormal distribution observed in the COTDR data within a month, this study classified the warning levels for each segment of the fiber optic system. The higher the frequency of abnormalities, the more frequent the occurrence of third-party damage activities during that period, resulting in a higher warning level.…”

Section: Case Studymentioning

confidence: 99%

See 1 more Smart Citation

Integrated Risk Assessment of Mountainous Long-Distance Oil and Gas Pipelines Based on Multisource Spatial Data

Wang,

Li,

Zhu

et al. 2024

ACS Omega

View full text Add to dashboard Cite

Pipeline risk assessment is crucial for pipeline safety management and operation. The aim of this study is to develop a comprehensive assessment model that accurately evaluates pipeline risks and ensures the safe and reliable operation of the pipeline system. The model is based on multisource spatial data and is primarily applicable to long-distance oil and gas pipelines that traverse complex geological conditions in mountainous areas. The research is conducted using the example of the Jinliwen natural gas pipeline in Zhejiang Province, China. By analyzing the geological data of the study area and the potential risks that the pipeline may encounter, a comprehensive risk assessment indicator system for the pipeline was developed using slope units to divide pipeline sections. The pipeline risk levels are classified using the K-means clustering-entropy weighted-random forest algorithm. The model is evaluated using accuracy (Acc), precision (Pre), recall (R), F1-score, and the ROC curve. The results show that the model has an accuracy of 0.917, a precision of 0.92, a recall of 0.916, an F1-score of 0.914, and an AUC (Area Under Curve) of 0.93, indicating its strong predictive capability. The risk assessment results demonstrate a strong consistency when compared with actual incident events. This indicates that the constructed model effectively reflects the influencing factors of pipeline risk, providing a basis for pipeline risk assessment and disaster prevention and mitigation efforts in similar regions.

show abstract

Section: Case Studymentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

Integrated Risk Assessment of Mountainous Long-Distance Oil and Gas Pipelines Based on Multisource Spatial Data

Wang,

Li,

Zhu

et al. 2024

ACS Omega

View full text Add to dashboard Cite

show abstract

“…Distributed fiber-optic sensors (DFOS) are a type of sensing technology that allows for continuous real-time monitoring of objects or structures. DFOS system uses optical fiber as sensing element to detect changes in the surrounding environment, such as temperature and applied mechanical stresses [1][2][3]. Particularly fiber-optical distributed acoustic sensing (DAS) systems are useful for facility security because it can detect and locate potential threats, such as unauthorized access [4,5].…”

Section: Introductionmentioning

confidence: 99%

Potential possibilities of voice image recognition by the analysis of distributed fiber-optic sensor signals

Gureev,

Gubareva,

Dashkov

et al. 2023

Optical Technologies for Telecommunications 2022

View full text Add to dashboard Cite

This study aimed to investigate the potential application of distributed fiber-optic acoustic sensors for speech recognition amidst complex audio backgrounds. The experimental measurements were carried out on the mock-up room with a fiberoptic link. The possibility of application the fiber-optic distributed acoustic sensor for localization of sound source and recognition of musical and human speech signals amidst complex audio backgrounds was demonstrated. The signal detected by DAS provides good quality of music composition recognition and clear speech recognition. The difference in spectrum of signals detected by microphone and DAS was analyzed. The signal noise ratios were calculated for test speech signal with different average levels and its influence on the speech recognition was analyzed.

show abstract

“…The optical fibers are then run along the surface of the steel cage and are connected to the strain gauges. This allows for the monitoring of the strain on the steel cage, which can be used to infer the strain on the surrounding concrete [195].…”

mentioning

confidence: 99%

Exploring the Potential of Promising Sensor Technologies for Concrete Structural Health Monitoring

Shilar,

Ganachari,

Patil

et al. 2024

Materials

View full text Add to dashboard Cite

Structural health monitoring (SHM) is crucial for maintaining concrete infrastructure. The data collected by these sensors are processed and analyzed using various analysis tools under different loadings and exposure to external conditions. Sensor-based investigation on concrete has been carried out for technologies used for designing structural health monitoring sensors. A Sensor-Infused Structural Analysis such as interfacial bond-slip model, corroded steel bar, fiber-optic sensors, carbon black and polypropylene fiber, concrete cracks, concrete carbonation, strain transfer model, and vibrational-based monitor. The compressive strength (CS) and split tensile strength (STS) values of the analyzed material fall within a range from 26 to 36 MPa and from 2 to 3 MPa, respectively. The material being studied has a range of flexural strength (FS) and density values that fall between 4.5 and 7 MPa and between 2250 and 2550 kg/m3. The average squared difference between the predicted and actual compressive strength values was found to be 4.405. With cement ratios of 0.3, 0.4, and 0.5, the shear strength value ranged from 4.4 to 5.6 MPa. The maximum shear strength was observed for a water–cement ratio of 0.4, with 5.5 MPa, followed by a water–cement ratio of 0.3, with 5 MPa. Optimizing the water–cement ratio achieves robust concrete (at 0.50), while a lower ratio may hinder strength (at 0.30). PZT sensors and stress-wave measurements aid in the precise structural monitoring, enhanced by steel fibers and carbon black, for improved sensitivity and mechanical properties. These findings incorporate a wide range of applications, including crack detection; strain and deformation analysis; and monitoring of temperature, moisture, and corrosion. This review pioneers sensor technology for concrete monitoring (Goal 9), urban safety (Goal 11), climate resilience (Goal 13), coastal preservation (Goal 14), and habitat protection (Goal 15) of the United Nations’ Sustainable Development Goals.

show abstract

Brillouin fiber optic sensors and mobile augmented reality-based digital twins for quantitative safety assessment of underground pipelines

Cited by 42 publications

References 61 publications

Integrated Risk Assessment of Mountainous Long-Distance Oil and Gas Pipelines Based on Multisource Spatial Data

Integrated Risk Assessment of Mountainous Long-Distance Oil and Gas Pipelines Based on Multisource Spatial Data

Potential possibilities of voice image recognition by the analysis of distributed fiber-optic sensor signals

Exploring the Potential of Promising Sensor Technologies for Concrete Structural Health Monitoring

Contact Info

Product

Resources

About