scholarly journals Monitoring urban hydrological environment monitoring using fiber optical sensing

2020 ◽  
Author(s):  
Kai Gao ◽  
Lianjie Huang ◽  
Carly Donahue ◽  
Jonathan Ajo-Franklin
Keyword(s):  
Optical Sensing ◽  
Environment Monitoring ◽  
Fiber Optical ◽  
Hydrological Environment

First Proof That Geographic Location on Deployed Fiber Cable Can Be Determined by Using OTDR Distance Based on Distributed Fiber Optical Sensing Technology

2020 ◽  
Author(s):  
Tiejun J. Xia ◽  
Glenn A. Wellbrock ◽  
Ming-Fang Huang ◽  
Milad Salemi ◽  
Yuheng Chen ◽  
...  
Keyword(s):  
Optical Sensing ◽  
Geographic Location ◽  
Sensing Technology ◽  
Fiber Optical

Monitoring deformation and damage on rock structures with distributed fiber optical sensing

2004 ◽  
Vol 41 (3) ◽  
pp. 413 ◽  
Author(s):  
J. Chai ◽  
S.M. Wei ◽  
X.T. Chang ◽  
J.X. Liu
Keyword(s):  
Optical Sensing ◽  
Fiber Optical

Multi-Channel Fiber Optical Sensing System for Urban Bridge Cluster Health Monitoring

2012 ◽  
Vol 557-559 ◽  
pp. 2075-2080
Author(s):  
Yi Li ◽  
Zhong Guo ◽  
Yi Qiang Xiang
Keyword(s):  
Health Monitoring ◽  
Optical Sensing ◽  
Measurement Data ◽  
Traffic Load ◽  
Sensor Data ◽  
Effect Of Temperature ◽  
Seismic Safety ◽  
Sensing System ◽  
Fiber Optical ◽  
Strain Responses

Modern technologies are increasingly facilitating real-time monitoring of urban bridges and transportation networks. The advances in multi-channel fiber optical sensing system for instance, enable practical deployments for large extended bridge structural systems. Sensor data, can be used for long-term condition assessment, traffic-load regulation, emergency response, and seismic safety applications. In this paper, A flexible and scalable urban bridge Cluster Health Monitoring system is being developed and implemented. A typical concrete tied arch bridge was selected to introduce the computer-based automated signal analysis algorithms to process the monitoring data and one-year measurement data obtained from the fiber optical strain and temperature sensors are used for this study. The correlation analysis technique is applied to quantify the effect of temperature on the strain responses. The results show that the linear regression model exhibits good capabilities for mapping the strain responses with temperature.

Application of Zinc Sulfide Quantum Dots for Optical Sensing

2019 ◽  
Vol 806 ◽  
pp. 186-191
Author(s):  
Alexander A. Sergeev ◽  
Andrey A. Leonov ◽  
Anna N. Galkina ◽  
Sergey S. Voznesenskiy
Keyword(s):  
Quantum Dots ◽  
Zinc Sulfide ◽  
Optical Sensing ◽  
Aqueous Media ◽  
Sensory Systems ◽  
Sensory Characteristics ◽  
Sensory Response ◽  
Aqueous Environment ◽  
Environment Monitoring

The luminescent sensory systems based on manganese-doped zinc sulfide quantum dots were developed for aqueous environment monitoring. The structural, optical and sensory characteristics of quantum dots were investigated. The mechanism of ZnS:Mn2+ interaction with methane in the aqueous media, as well as factors that have a primary influence on the formation of the sensory response in the reaction with methane, were determined.

Combined fiber optical confocal microscopy for noninvasive optical sensing

2003 ◽  
Author(s):  
Ilko K. Ilev ◽  
Ronald W. Waynant ◽  
Erik Gorman ◽  
Reggie Luedtke ◽  
Kimberly R. Byrnes ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Optical Sensing ◽  
Fiber Optical

SBS-Based Fiber Optical Sensing Using Frequency-Domain Simultaneous Tone Interrogation

2011 ◽  
Vol 29 (11) ◽  
pp. 1729-1735 ◽  
Author(s):  
Asher Voskoboinik ◽  
Jian Wang ◽  
Bishara Shamee ◽  
Scott R. Nuccio ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Optical Sensing ◽  
Fiber Optical

Monitoring deformation and damage on rock structures with distributed fiber optical sensing

2004 ◽  
Vol 41 ◽  
pp. 298-303 ◽  
Author(s):  
J Chai ◽  
S.M Wei ◽  
X.T Chang ◽  
J.X Liu
Keyword(s):  
Optical Sensing ◽  
Fiber Optical

scholarly journals Intrusion location technology of Sagnac distributed fiber optical sensing system based on deep learning

2021 ◽  
pp. 1-1
Author(s):  
Jinyi Wu ◽  
Rusheng Zhuo ◽  
Shengpeng Wan ◽  
Xinzhong Xiong ◽  
Xinliang Xu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optical Sensing ◽  
Sensing System ◽  
Fiber Optical
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