Fast and high spatial resolution distributed optical fiber sensor

Noghani, Fereshteh Esmailzadeh; Tofighi, Sara; Pishbin, Nafiseh; Bahrampour, Abbas

doi:10.1016/j.optlastec.2019.02.033

Cited by 15 publications

(7 citation statements)

References 30 publications

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“…Herein the heating rate of 7.5°C/min was set by considering the preliminary shape memory experiments of the used SMPC material. However, the DOFS are capable of acquiring data in a pico‐second with a sub‐centimeter spatial resolution and for a kilometer level dynamic range 38 . Therefore, the DOSFs can be used to measure higher heating rates on demand.…”

Section: Resultsmentioning

confidence: 99%

Distributed sensing based real‐time process monitoring of shape memory polymer components

Herath

Emmanuel

Jeewantha

et al. 2022

J of Applied Polymer Sci

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Shape memory polymer (SMP) materials have the capacity to undergo large deformations imposed by mechanical loading, hold a temporary shape, and then recover their original shape upon exposure to a particular external stimulus. The fiber reinforced shape memory polymer composites (SMPCs) with enhanced structural performances give a boost to breakthrough technologies for large-scale engineering applications. This article presents a novel technique for distributed optical fiber sensor (DOFS) embedded SMPCs intended for realtime process monitoring of large-scale engineering applications such as deployable space structures. Herein a carbon fiber reinforced SMPC was tested under a three-point flexural shape memory process and the DOFS data were acquired through optical backscatter reflectometry. Experiments were conducted in a temperature controlled thermal chamber coupled with a 10 kN electromechanical testing system. DOFSs offered unique advantages for spatially distributed dynamic temperature and strain measurements during the shape memory process. Compared to the standard test method dynamic mechanical analysis, larger samples can be tested effectively by using a single DOFS with large strain levels and shape complexity. The proposed technique demonstrated the ability of embedded DOFSs for in-situ shape memory characterization such as shape fixity ratio, shape recovery ratio and recovery rate. This technique will eliminate the challenges hindering the process monitoring and performance evaluation of large SMPC components operating in their real working environments.

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Section: Resultsmentioning

confidence: 99%

Distributed sensing based real‐time process monitoring of shape memory polymer components

Herath

Emmanuel

Jeewantha

et al. 2022

J of Applied Polymer Sci

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“…Brillouin optical time-domain analysis (BOTDA) employs a more complex method known as stimulated Brillouin scattering (SBS). Esmailzadeh Noghani et al 26 proposed a novel method called the multiple short pulse BOTDA (MSP-BOTDA) which yielded sub-centimetre spatial resolution and kilometre dynamic range simultaneously. This technique can detect a wide range of temperature/strain changes as the effective Brillouin gain bandwidth of the pump pulse train is greater.…”

Section: Strain-based Methodsmentioning

confidence: 99%

“…In DFOS, scattering is the interaction between light and an optical medium. Raman, 27,30 Brillouin 17,26,33,85 and Rayleigh 17,29 scattering are the three modes of scattering that occur in DFOS. Raman scattering is influenced by the temperature of the fiber, and Brillouin scattering depends on the fiber density, which is directly related to the temperature and strain change of the optical fibre.…”

Section: Health Monitoring Of Composite Structuresmentioning

confidence: 99%

“…17 Multiplexing capability, higher sensitivity, electro-magneto immunity and durability have made fibre Bragg grating (FBG) sensors [18][19][20][21][22] an attractive candidate for the real-time monitoring of aircraft structures. [23][24][25] Distributed fibre optic sensing (DFOS) 26 technology capable of obtaining strain measurements along the entire length of the fibre has been developed significantly over the last decade and is being used in large structures like bridges, high-rise buildings and tunnels. 1 Strain, temperature and vibration are the physical parameters monitored for damage detection in fibre optic sensing techniques.…”

Section: Introductionmentioning

confidence: 99%

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Sensory methods and machine learning based damage identification of fibre-reinforced composite structures: An introductory review

Bandara

Herath

Epaarachchi

2022

Journal of Reinforced Plastics and Composites

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Fibre-reinforced composite materials are extensively used for manufacturing critical engineering components in diverse applications, which demands intelligent and reliable structural health monitoring (SHM) schemes to prevent catastrophic failures associated with composite structures. Composite materials have complex failure mechanisms, and it is essential to employ reliable SHM methods with high accuracy to detect damages at the incipient stage. Although there are several SHM technologies available, no single strategy is impeccable for tackling all damage types due to the incredibly complex failure mechanisms of the composite materials. Machine learning (ML) methods are frequently integrated to compensate for the limitations of the traditional SHM methods. This paper presents the state-of-the-art sensory methods and deep learning (DL) techniques while emphasizing the future directions for the engineering and scientific community interested in developing novel SHM systems for fibre-reinforced polymer composite structures intended for civil, aerospace, automotive, marine, oil and gas exploration industries.

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“…Among these three fields, structural safety monitoring and perimeter intrusion detection are of more concern than fire monitoring due to the diversification of demand. For long-distance monitoring needs, especially for subway tunnels, distributed fiber-optic sensing technology has been widely recognized as the most promising means of addressing complex needs due to its advantages of large-scale monitoring, high sensitivity, and multiplexing capabilities [12]. For instance, the safety monitoring of subway structures based on Brillouin optical time domain reflectometry (BOTDR) technology [13] has been reported [14,15].…”

Section: Introductionmentioning

confidence: 99%

A Novel Monitoring Approach for Train Tracking and Incursion Detection in Underground Structures Based on Ultra-Weak FBG Sensing Array

Nan

Yi-qiang

et al. 2019

Sensors

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Tracking operating trains and identifying illegal intruders are two important and critical issues in subway safety management. One challenge is to find a reliable methodology that would enable these two needs to be addressed with high sensitivity and spatial resolution over a long-distance range. This paper proposes a novel monitoring approach based on distributed vibration, which is suitable for both train tracking and incursion detection. For an actual subway system, ultra-weak fiber Bragg grating (FBG) sensing technology was applied to collect the distributed vibration responses from moving trains and intruders. The monitoring data from the subway operation stage were directly utilized to evaluate the feasibility of the proposed method for tracking trains. Moreover, a field simulation experiment was performed to validate the possibility of detecting human intrusion. The results showed that the diagonal signal pattern in the distributed vibration response can be used to reveal the location and speed of the moving loads (e.g., train and intruders). Other train parameters, such as length and the number of compartments, can also be obtained from the vibration responses through cross-correlation and envelope processing. Experimental results in the time and frequency domains within the selected intrusion range indicated that the proposed method can distinguish designed intrusion cases in terms of strength and mode.

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Fast and high spatial resolution distributed optical fiber sensor

Cited by 15 publications

References 30 publications

Distributed sensing based real‐time process monitoring of shape memory polymer components

Distributed sensing based real‐time process monitoring of shape memory polymer components

Sensory methods and machine learning based damage identification of fibre-reinforced composite structures: An introductory review

A Novel Monitoring Approach for Train Tracking and Incursion Detection in Underground Structures Based on Ultra-Weak FBG Sensing Array

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