LPG Interrogator Based on FBG Array and Artificial Neural Network

Barino, Felipe Oliveira; Santos, Alexandre Bessa dos

doi:10.1109/jsen.2020.3007957

Cited by 18 publications

(2 citation statements)

References 26 publications

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“…A growing interest has been in integrating machine learning (ML) techniques into optical FBG sensing systems. For example, some researchers investigated using neural networks for peak tracking [20][21][22][23]. Additionally, other researchers recently investigated using machine learning algorithms with the optical FBG sensors for leakage detection, subway track vibration sensing, liquid level estimation, and temperature sensing [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Strain FBG-Based Sensor for Detecting Fence Intruders Using Machine Learning and Adaptive Thresholding

Elleathy,

Alhumaidan,

Alqahtani

et al. 2023

Sensors

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This paper demonstrates an intruder detection system using a strain-based optical fiber Bragg grating (FBG), machine learning (ML), and adaptive thresholding to classify the intruder as no intruder, intruder, or wind at low levels of signal-to-noise ratio. We demonstrate the intruder detection system using a portion of a real fence manufactured and installed around one of the engineering college’s gardens at King Saud University. The experimental results show that adaptive thresholding can help improve the performance of machine learning classifiers, such as linear discriminant analysis (LDA) or logistic regression algorithms in identifying an intruder’s existence at low optical signal-to-noise ratio (OSNR) scenarios. The proposed method can achieve an average accuracy of 99.17% when the OSNR level is <0.5 dB.

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Section: Introductionmentioning

confidence: 99%

Strain FBG-Based Sensor for Detecting Fence Intruders Using Machine Learning and Adaptive Thresholding

Elleathy,

Alhumaidan,

Alqahtani

et al. 2023

Sensors

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“…The numbers of sensors required in such applications have also been increased significantly to ensure that the accuracy of sensor data monitoring does not decrease. FBG is characterized by easy network measurement, large capacity multiplexing, and wavelength demodulation [5][6][7][8]. It can be used in optical fiber sensor networks for monitoring large-scale engineering applications, which have strict requirements for the reliability of FBG sensor networks.…”

Section: Introductionmentioning

confidence: 99%

Self-Healing and Shortest Path in Optical Fiber Sensor Network

Mao

et al. 2022

Journal of Sensors

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In this study, a new square-based fiber Bragg grating (FBG) sensor network model is proposed to address possible link failures in FBG sensor networks and improve their reliability. Graph theory and optical switching are simultaneously applied to these sensor networks to improve their self-healing ability; the FBG sensor network is regarded as a directed graph. Three commonly used self-short-circuit algorithms are compared in terms of the self-healing capabilities that they provide to the optical fiber sensor network. Among these, the shortest-path faster algorithm achieved a high, nearly 90% repair accuracy and had an average repair time of 0.103 s, the shortest in this study. The newly designed FBG self-healing network can be reorganized and repaired when local damage occurs, thereby improving its reliability.

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