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High-temperature measurements above 1000 °C are critical in harsh environments such as aerospace, metallurgy, fossil fuel, and power production. Fiber-optic high-temperature sensors are gradually replacing traditional electronic sensors due to their small size, resistance to electromagnetic interference, remote detection, multiplexing, and distributed measurement advantages. This paper reviews the sensing principle, structural design, and temperature measurement performance of fiber-optic high-temperature sensors, as well as recent significant progress in the transition of sensing solutions from glass to crystal fiber. Finally, future prospects and challenges in developing fiber-optic high-temperature sensors are also discussed.

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A data-driven-based methodology for SHM in reinforced concrete structures using embedded fiber optic sensors and pattern recognition techniques is presented. A prototype of a reinforced concrete structure was built and instrumented in a novel fashion with FBGs bonded directly to the reinforcing steel bars, which, in turn, were embedded into the concrete structure. The structure was dynamically loaded using a shaker. Superficial positive damages were induced using bonded thin steel plates. Data for pristine and damaged states were acquired. Classifiers based on Mahalanobis' distance of the covariance data matrix were developed for both supervised and unsupervised pattern recognition with an accuracy of up to 98%. It was demonstrated that the proposed sensing scheme in conjunction with the developed supervised and unsupervised pattern recognition techniques allows the detection of slight stiffness changes promoted by damages, even when strains are very small and the changes of these associated with the damage occurrence may seem negligible.

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Femtosecond (fs) laser written fiber Bragg gratings (FBGs) are excellent candidates for ultra-high temperature (>800 ºC) monitoring. More specifically, Type II modifications in silicate glass fibers, characterized by the formation of self-organized birefringent nanostructures, are known to exhibit remarkable thermal stability around 1000 ºC for several hours. However, to date there is no clear understanding on how both laser writing parameters and glass composition impact the overall thermal stability of these fiber-based sensors. In this context, this work investigates thermal stability of Type II modifications in various conventional glass systems (including pure silica glasses with various Cl and OH contents, GeO2-SiO2 binary glasses, TiO2- and B2O3-doped commercial glasses) and with varying laser parameters (writing speed, pulse energy). In order to monitor thermal stability, isochronal annealing experiments (Δt⁓ 30 min, ΔT⁓ 50 ºC) up to 1400 ºC were performed on the irradiated samples, along with quantitative retardance measurements. Among the findings to highlight, it was established that ppm levels of Cl and OH can drastically reduce thermal stability (by about 200 ºC in this study). Moreover, GeO2 doping up to 17 mole% only has a limited impact on thermal stability. Finally, the relationships between glass viscosity, dopants/impurities, and thermal stability, are discussed.

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BACKGROUND AND OBJECTIVE: Monitoring of changes in respiratory rate provides information on a patient's psychophysical state. This paper presents a respiratory rate detection method based on analysis of signals from a fiber Bragg grating (FBG)-based sensor. METHODS: The detection method is based on a system of software blocks that identify notches in the signal waveforms, determine their parameters, and then transmit them to the classifier, which decides which of them are the characteristic waves of the respiratory cycle. The classifier of respiratory waves was developed by means of machine learning methods and using the training data obtained from 10 volunteers (7 males, 3 females, age: 41.1 ±â€¯8.28 years, weight: 73.6 ±â€¯15.25 kg, height 173.5 ±â€¯6.43 cm), who were lying in the tube of a 3-Tesla magnetic resonance imaging (MRI) scanner. RESULTS: In the verification study, aimed at assessing the performance of the method for detecting respiratory rate, 15 subjects (14 males, 1 female, age: 20.2 ±â€¯3.00 years, weight: 75.47 ± 10.58 kg, height 179.13 ± 6.27 cm) were involved. Clinically satisfactory results of respiratory rate detection were obtained: root mean square error of 1.48 rpm and the limits of agreement at -2.73 rpm and 3.04 rpm. The results indicate a high efficiency of the classifier, i.e., sensitivity: 96.50 ± 3.44%, precision: 95.42 ± 2.84%, and accuracy: 92.99 ± 3.37%. CONCLUSION: The all-dielectric sensor acquires the respiration curve and the proposed scheme of computation enables for extracting respiratory rate automatically and continuously. This scheme based on machine learning procedures will be integrated into a system to facilitate non-invasive continuous monitoring of MRI patients.

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Each year 35,000 cardiac ablation procedures are performed to treat atrial fibrillation through the use of catheter systems. The success rate of this treatment is highly dependent on the force which the catheter applies on the heart wall. If the magnitude of the applied force is much higher than a certain threshold the tissue perforates, whereas if the force is lower than this threshold the lesion size may be too large and is inconsistent. Furthermore, studies have shown large variability in the applied force from trained physicians during treatment, suggesting that physicians are unable to manually regulate the levels of the force at the site of treatment. Current catheter systems do not provide the physicians with active means for contact force control and are only at most aided by visual feedback of the forces measured in situ. This paper discusses a novel design of a robotic end-effector that integrates mechanisms of sensing and actively controlling of the applied forces into a miniaturized compact form. The required specifications for design and integration were derived from the current application under investigation. An off-the-shelf miniature piezoelectric motor was chosen for actuation, and a force sensing solution was developed to meet the specifications. Experimental characterization of the actuator and the force sensor within the integrated setup show compliance with the specifications and pave the way for future experimentation where closed-loop control of the system can be implemented according to the contact force control strategies for the application.

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This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil.

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This paper presents an overview of optical fiber sensor networks for remote sensing. Firstly, the state of the art of remote fiber sensor systems has been considered. We have summarized the great evolution of these systems in recent years; this progress confirms that fiber-optic remote sensing is a promising technology with a wide field of practical applications. Afterwards, the most representative remote fiber-optic sensor systems are briefly explained, discussing their schemes, challenges, pros and cons. Finally, a synopsis of the main factors to take into consideration in the design of a remote sensor system is gathered.

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We propose and demonstrate two ultra-long range fiber Bragg grating (FBG) sensor interrogation systems. In the first approach four FBGs are located 200 km from the monitoring station and a signal to noise ratio of 20 dB is obtained. The second improved version is able to detect the four multiplexed FBGs placed 250 km away, offering a signal to noise ratio of 6-8 dB. Consequently, this last system represents the longest range FBG sensor system reported so far that includes fiber sensor multiplexing capability. Both simple systems are based on a wavelength swept laser to scan the reflection spectra of the FBGs, and they are composed by two identical-lengths optical paths: the first one intended to launch the amplified laser signal by means of Raman amplification and the other one is employed to guide the reflection signal to the reception system.

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