Inscription of Bragg gratings in undoped PMMA mPOF with Nd:YAG laser at 266 nm wavelength

Min, Rui; Pereira, Luí­s; Paixão, Tiago; Woyessa, Getinet; André, Paulo; Bang, Ole; Antunes, Paulo; Pinto, João; Li, Zhaohui; Ortega, B.; Marques, Carlos

doi:10.1364/oe.27.038039

Cited by 36 publications

(17 citation statements)

References 38 publications

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“…It was also confirmed from the experiment performed that even after prestraining the fiber the following strain applied could be effectively calculated in real-time therefore prestraining was not an issue in this case. Recently, polymer such as PMMA, 85 cyclic-olefin copolymer (TOPAS 86,87 and Zeonex 88 ), polycarbonate 89 -based FBG has taken over conventional silica-based FBG because of its distinctive material properties such as low Young's modulus and high fracture toughness that can be effectively used in enhancing strain performance of sensor. Inscription of gratings in such polymers can be made using 248-nm KrF laser 90 for stable grating, and ultrafast gratings in 7 ms were formed on PMMA using dopant (diphenyl disulphide) as discussed in Ref.…”

Section: Fbg-based Strain Sensorsmentioning

confidence: 99%

Fiber Bragg grating sensors for monitoring of physical parameters: a comprehensive review

2020

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Fiber Bragg grating has embraced the area of fiber optics since the early days of its discovery, and most fiber optic sensor systems today make use of fiber Bragg grating technology. Researchers have gained enormous attention in the field of fiber Bragg grating (FBG)-based sensing due to its inherent advantages, such as small size, fast response, distributed sensing, and immunity to the electromagnetic field. Fiber Bragg grating technology is popularly used in measurements of various physical parameters, such as pressure, temperature, and strain for civil engineering, industrial engineering, military, maritime, and aerospace applications. Nowadays, strong emphasis is given to structure health monitoring of various engineering and civil structures, which can be easily achieved with FBG-based sensors. Depending on the type of grating, FBG can be uniform, long, chirped, tilted or phase shifted having periodic perturbation of refractive index inside core of the optical fiber. Basic fundamentals of FBG and recent progress of fiber Bragg grating-based sensors used in various applications for temperature, pressure, liquid level, strain, and refractive index sensing have been reviewed. A major problem of temperature cross sensitivity that occurs in FBG-based sensing requires temperature compensation technique that has also been discussed in this paper.

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Section: Fbg-based Strain Sensorsmentioning

confidence: 99%

Fiber Bragg grating sensors for monitoring of physical parameters: a comprehensive review

2020

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“…To fabricate the FBGs, the phase mask technique described in [ 29 ] was employed. Briefly, a photosensitive single-mode fiber (ThorLabs GF1B) was inscribed using a nanosecond-pulsed Nd:YAG laser emitting at 266 nm (LOTIS TII LS-2137ULaser) with an 8 ns pulse time.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…Thus, the Peltier plate was not a component of the sensor system, which was only comprised of the FBGs and, therefore, could be used in the classified areas. To fabricate the FBGs, the phase mask technique described in [29] was employed. Briefly, a photosensitive single-mode fiber (ThorLabs GF1B) was inscribed using a nanosecond-pulsed Nd:YAG laser emitting at 266 nm (LOTIS TII LS-2137ULaser) with an 8 ns pulse time.…”

Section: Methodsmentioning

confidence: 99%

FBG-Based Temperature Sensors for Liquid Identification and Liquid Level Estimation via Random Forest

Pereira

Coimbra

Lazaro

et al. 2021

Sensors

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This paper proposed a liquid level measurement and classification system based on a fiber Bragg grating (FBG) temperature sensor array. For the oil classification, the fluids were dichotomized into oil and nonoil, i.e., water and emulsion. Due to the low variability of the classes, the random forest (RF) algorithm was chosen for the classification. Three different fluids, namely water, mineral oil, and silicone oil (Kryo 51), were identified by three FBGs located at 21.5 cm, 10.5 cm, and 3 cm from the bottom. The fluids were heated by a Peltier device placed at the bottom of the beaker and maintained at a temperature of 318.15 K during the entire experiment. The fluid identification by the RF algorithm achieved an accuracy of 100%. An average root mean squared error (RMSE) of 0.2603 cm, with a maximum RMSE lower than 0.4 cm, was obtained in the fluid level measurement also using the RF algorithm. Thus, the proposed method is a feasible tool for fluid identification and level estimation under temperature variation conditions and provides important benefits in practical applications due to its easy assembly and straightforward operation.

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“…For the experiments performed in this paper, one FBG was inscribed with a phase mask technique, described in [ 29 , 30 ]. The inscription used a nanosecond-pulsed Nd:YAG laser LS-2137U, emitting at 266 nm, with an 8 ns pulse time (LOTIS TII, Minsk, Belarus) in order to produce periodic modulation in the refractive index of the core of a photosensitive single-mode fiber GF1B (ThorLabs, Newton, NJ, USA).…”

Section: Materials and Methodsmentioning

confidence: 99%

FBG-Based Sensor for the Assessment of Heat Transfer Rate of Liquids in a Forced Convective Environment

Lazaro

Frizera

Marques

et al. 2021

Sensors

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The assessment of heat transfer is a complex task, especially for operations in the oil and gas industry, due to the harsh and flammable workspace. In light of the limitations of conventional sensors in harsh environments, this paper presents a fiber Bragg grating (FBG)-based sensor for the assessment of the heat transfer rate (HTR) in different liquids. To better understand the phenomenon of heat distribution, a preliminary analysis is performed by constructing two similar scenarios: those with and without the thermal insulation of a styrofoam box. The results indicate the need for a minimum of thermal power to balance the generated heat with the thermal losses of the setup. In this minimum heat, the behavior of the thermal distribution changes from quadratic to linear. To assess such features, the estimation of the specific heat capacity and the thermal conductivity of water are performed from 3 W to 12 W, in 3 W steps, resulting in a specific heat of 1.144 cal/g °C and thermal conductivity of 0.5682 W/m °C. The calibration and validation of the HTR sensor is performed in a thermostatic bath. The method, based on the temperature slope relative to the time curve, allowed for the measurement of HTR in water and Kryo 51 oil, for different heat insertion configurations. For water, the HTR estimation was 308.782 W, which means an uncertainty of 2.8% with the reference value of the cooling power (300 W). In Kryo 51 oil, the estimated heat absorbed by the oil was 4.38 kW in heating and 718.14 kW in cooling.

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Inscription of Bragg gratings in undoped PMMA mPOF with Nd:YAG laser at 266 nm wavelength

Cited by 36 publications

References 38 publications

Fiber Bragg grating sensors for monitoring of physical parameters: a comprehensive review

Fiber Bragg grating sensors for monitoring of physical parameters: a comprehensive review

FBG-Based Temperature Sensors for Liquid Identification and Liquid Level Estimation via Random Forest

FBG-Based Sensor for the Assessment of Heat Transfer Rate of Liquids in a Forced Convective Environment

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