Intelligent monitoring of spatially-distributed cracks using distributed fiber optic sensors assisted by deep learning
Published 2023 View Full Article
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Title
Intelligent monitoring of spatially-distributed cracks using distributed fiber optic sensors assisted by deep learning
Authors
Keywords
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Journal
MEASUREMENT
Volume 220, Issue -, Pages 113418
Publisher
Elsevier BV
Online
2023-08-06
DOI
10.1016/j.measurement.2023.113418
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- (2021) Soroush Mahjoubi et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Crack monitoring in reinforced concrete beams by distributed optical fiber sensors
- (2020) Carlos G. Berrocal et al. Structure and Infrastructure Engineering
- Deep learning method for detection of structural microcracks by brillouin scattering based distributed optical fiber sensors
- (2020) Qingsong Song et al. Smart Materials and Structures
- Automatic railroad track components inspection using real‐time instance segmentation
- (2020) Feng Guo et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Crack monitoring and damage assessment of BFRP-jacketed concrete cylinders under compression load based on acoustic emission techniques
- (2020) Gao Ma et al. CONSTRUCTION AND BUILDING MATERIALS
- Measuring crack width using a distributed fiber optic sensor based on optical frequency domain reflectometry
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- A deep learning-based framework for an automated defect detection system for sewer pipes
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- A new measurement approach for deflection monitoring of large-scale bored piles using distributed fiber sensing technology
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- Focal loss for dense object detection
- (2018) Tsung-Yi Lin et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- (2017) Shaoqing Ren et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A Review of Distributed Optical Fiber Sensors for Civil Engineering Applications
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- Distributed fiber optic monitoring and stability analysis of a model slope under surcharge loading
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- Theoretical and Experimental Investigations into Crack Detection with BOTDR-Distributed Fiber Optic Sensors
- (2013) Xin Feng et al. JOURNAL OF ENGINEERING MECHANICS
- LabelMe: Online Image Annotation and Applications
- (2010) Antonio Torralba et al. PROCEEDINGS OF THE IEEE
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