• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.24-30
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• 2022

Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.

• Current Optics and Photonics
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• v.7 no.5
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• pp.511-517
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• 2023

Pipelines play an important role in urban water supply and drainage, oil and gas transmission, etc. This paper presents a technique for pattern recognition of fiber optic vibration signals collected by a distributed vibration sensing (DVS) system using a deep learning residual network (ResNet). The optical fiber is laid on the pipeline, and the signal is collected by the DVS system and converted into a 64 × 64 single-channel grayscale image. The grayscale image is input into the ResNet to extract features, and finally the K-nearest-neighbors (KNN) algorithm is used to achieve the classification and recognition of pipeline damage.

• Smart Structures and Systems
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• v.3 no.4
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• pp.475-494
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• 2007

This paper deals with the development of an innovative distributed construction system based on smart prefabricated concrete elements for the real-time condition assessment of civil infrastructure. So far, two reduced-scale prototypes have been produced, each consisting of a $0.2{\times}0.3{\times}5.6$ m RC beam specifically designed for permanent instrumentation with 8 long-gauge Fiber Optic Sensors (FOS) at the lower edge. The sensing system is Fiber Bragg Grating (FBG)-based and can measure finite displacements both static and dynamic with a sample frequency of 625 Hz per channel. The performance of the system underwent validation in the laboratory. The scope of the experiment was to correlate changes in the dynamic response of the beams with different damage scenarios, using a direct modal strain approach. Each specimen was dynamically characterized in the undamaged state and in various damage conditions, simulating different cracking levels and recurrent deterioration scenarios, including cover spalling and corrosion of the reinforcement. The location and the extent of damage are evaluated by calculating damage indices which take account of changes in frequency and in strain-mode-shapes. The outcomes of the experiment demonstrate how the damage distribution detected by the system is fully compatible with the damage extent appraised by inspection.