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This article presents a comprehensive study on the impact of irradiation optical fiber cores with a femtosecond-pulsed laser, operating at a wavelength of 1030 nm, on the signal amplitude in Rayleigh scattering-based optical frequency domain reflectometry (OFDR). The experimental study involves two fibers with significantly different levels of germanium doping: the standard single-mode fiber (SMF-28) and the ultra-high numerical aperture fiber (UHNA7). The research findings reveal distinct characteristics of reflected and scattered light amplitudes as a function of pulse energy. Although different amplitude changes are observed for the examined fibers, both can yield an enhancement of amplitude. The paper further investigates the effect of fiber Bragg grating inscription on the overall amplitude of reflected light. The insights gained from this study could be beneficial for controlling the enhancement of light scattering amplitude in fibers with low or high levels of germanium doping. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive study on the impact of irradiation optical fiber cores with a femtosecond-pulsed laser, operating at a wavelength of 1030 nm, on the signal amplitude in Rayleigh scattering-based optical frequency domain reflectometry (OFDR). The experimental study involves two fibers with significantly different levels of germanium doping: the standard single-mode fiber (SMF-28) and the ultra-high numerical aperture fiber (UHNA7). The research findings reveal distinct characteristics of reflected and scattered light amplitudes as a function of pulse energy. Although different amplitude changes are observed for the examined fibers, both can yield an enhancement of amplitude. The paper further investigates the effect of fiber Bragg grating inscription on the overall amplitude of reflected light. The insights gained from this study could be beneficial for controlling the enhancement of light scattering amplitude in fibers with low or high levels of germanium doping.

Despite the promising application of Distributed Optical Fiber Sensors (DOFS) in monitoring damage in composite structures, their implementation outside academia is still unsatisfactory due to the lack of a systematic approach to assessing their damage detection performance. The existing tool developed for non-destructive evaluation, Probability of Detection (POD) curves, needs to be adapted for structural health monitoring applications to account for spatial and temporal dependency. Damage detection performance with DOFS is deeply related to the inherent variability sources of the system, the strain transfer properties of the optical fiber, and the loading conditions, which determine the damage-induced strain on the structure. This paper establishes a systematic approach based on the Length at Detection (LaD) method to qualify DOFS for damage detection in composites under different scenarios. Specifically, this study considers two DOFS with different strain transfer properties for monitoring delamination in carbon fiber reinforced polymers double-cantilever beam specimens under mode I quasi-static and fatigue loading. The POD curves derived from the LaD method confirm that this methodology can quantify the change in the detection performance due to the DOFS type and the loading conditions. The study also proposes a practical solution to compare POD curves obtained with different sample sizes, by introducing the concept of virtual specimens to simulate the lower confidence bound convergence. [ABSTRACT FROM AUTHOR]

Distributed fiber optic sensors (DFOS) can detect structural cracks and structural deformation with high accuracy and wide measurement range. This study monitors the segmental prestressed bent cap, assembled with a large key dry joint, based on optical fiber technology, and it allows the comparison of its damaging process with that of a monolithic cast in place counterpart. The obtained results, comprising cross-section strain distributions, longitudinal strain profiles, neutral axis location, crack pattern, and the damage process, show that the DFOS technology can be successfully used to analyze the complex working stress state of the segmental beam with shear key joints, both in the elastic range and at the ultimate load, and to successfully identify the changing characteristics of the stress state of the segmental capping beam model when elastic beam theory no longer applies. The DFOS data confirm that the shear key joint, as the weak point of the segmental cap beam, results in the high stress concentration area, and the damage rate is higher than that of the cast-in-place beam. The accurate monitoring by the DFOS allows for the realization that the damage occurs at the premature formation of a concentrated compression zone on the upper part of the shear key. [ABSTRACT FROM AUTHOR]

In this paper, we propose and demonstrate a damage detection technique based on the automatic classification of the Lamb wave signals acquired on a metallic plate. In the reported experiments, Lamb waves are excited in an aluminum plate through a piezoelectric transducer glued onto the monitored structure. The response of the monitored structure is detected through a high-resolution phase-sensitive optical time-domain reflectometer (ϕ-OTDR). The presence and location of a small perturbation, induced by placing a lumped mass of 5 g on the plate, are determined by processing the optical fiber sensor data through support vector machine (SVM) classifiers trained with experimental data. The results show that the proposed method takes full advantage of the multipoint sensing nature of the ϕ-OTDR technology, resulting in accurate damage detection and localization. [ABSTRACT FROM AUTHOR]

Distributed acoustic sensors (DASs) are able to monitor in real-time acoustic excitation and mechanical vibration of the external environment for many kilometers along the length of the optical fiber. In the oil industry, the technology allows the monitoring of well structural health, identifying flow profile, acquiring seismic data, updating reservoir information, and feeding geological models. The spatial resolution of DAS is a limiting factor on the quality of information gathered. In this article, we propose and analyze a novel method of measuring local dynamic strain of structures using DAS. The method uses serpentine configurations to measure the frequency spectrum of the in-phase strain signals at discrete regions of the structure, enabling DAS to determine, among other vibration parameters, the strain frequency response function (SFRF). An experimental study of the sensor application with different arrangements in a small structure has been performed. The structure in the experiment consists of a free–free aluminum beam of approximately 2.7 m. Experiment results show agreement with numerical results developed by the finite element method (FEM) and using reference sensors, demonstrating a significant improvement of the DAS SFRF accuracy using the serpentine configuration and up to 12.9 dB increase in peak-to-noise ratio (PNR) for low excitation forces. The recovered response enabled the reconstruction of mode shapes. [ABSTRACT FROM AUTHOR]

Owing to their high sensitivity with respect to external measurands, Rayleigh-based distributed optical fiber sensors (DOFS) find their way into applications in many industrial and academic sectors. To further transcend the limit of these sensors in terms of sensing range, low spatial resolution, speed and accuracy of the measurement, improving the signal-to-noise ratio (SNR) of the system plays a pivotal role. Out of the several existing techniques for enhancing the SNR, one such method, solely dedicated to the Rayleigh-based sensors, is through intrinsically increasing the backreflected signal of the fibers. The enhanced backreflected signal provided by such fibers, generally known as reflection-enhanced fibers (REF), is rigorously analyzed in the present work. It is inferred from the analysis that the enhanced signal is essentially accompanied by enhanced signal-dependent noises, which can adversely affect their performance. For instance, when a performance comparison is carried out between the REF and a standard single-mode fiber (SMF) under identical experimental conditions, due to their different intrinsic backreflected signal levels, the two fibers experience dissimilar noise regimes leading to an erroneous estimation of the performance of the former. This necessitates the optimization of the interrogation system and the experimental parameters while employing such fibers for specific sensing applications. Additionally, a distributed temperature measurement is presented by taking advantage of the enhanced SNR of a 100 m long REF exhibiting a sub-mK temperature uncertainty of 0.5 mK at metric spatial resolution yielding a sixfold improvement compared to the 3 mK uncertainty of an SMF.

Short-time Fourier transform (STFT) algorithm with Lorentzian fitting is popular in distributed Brillouin optical fiber sensors to acquire Brillouin frequency. However, STFT often suffers from the tradeoff between Brillouin frequency measurement resolution and computation complexity. To lower the complexity of Brillouin frequency analysis and speedup measurement, a novel method based on instantaneous frequency (IF) analysis is proposed. The instantaneous Brillouin frequency can be obtained through the instantaneous phase change between two adjacent samples in the time domain. The requirement on the spectral resolution is, therefore, greatly relaxed, significantly reducing computation complexity and lowering measurement time cost. A Brillouin optical time-domain reflectometry (BOTDR) scheme is demonstrated with a spatial resolution of 1.2 m over a 5-km sensing fiber. For an average count of 4096 over measurements, experiments show that the IF algorithm can reduce computation complexity by 122 times at a standard deviation (STD) of 0.5065 MHz for BFS estimation which is comparable to the STD obtained through STFT in conjunction with Lorentzian fitting. [ABSTRACT FROM AUTHOR]

To improve the understanding of failure mechanisms and behaviour of hard rock tunnel linings, local load conditions were experimentally simulated and monitored using a comprehensive set of sensors and imaging techniques. The data includes measurements from distributed optical fiber sensors (DOFS), high-resolution cameras, load cells, pressure cells and LVDTs. Two types of loads were examined: rock block load and bond loss combined with a distributed load over the area of lost bond. The experiments replicated these conditions and were conducted in a laboratory setting where the shotcrete and substrate rock were substituted by cast fiber reinforced concrete (FRC) and cast concrete, respectively. To facilitate the loads, concrete cones were cast into the substrate concrete and pushed through the FRC top layer with a hydraulic jack to mimic rock block loads. To simulate the bond loss and the associated distributed load, lifting bags were installed and inflated between the FRC layer and substrate cast concrete. All specimens were monitored using DOFS embedded in two perpendicular directions and in two layers in the top FRC layer. In addition, the hydraulic jack was instrumented with LVDTs and load cells to measure displacement and load, and the pressure in the lifting bags was monitored using a pressure cell. Two cameras continuously photographed the top surface of the FRC layer, which had been painted with a speckle pattern, during the testing and the pictures can be used for digital image correlation (DIC). Lastly, each specimen was scanned with a 3D scanner prior to and after testing of the specimen., (© 2024 The Author(s).)

In this study, corrosion-induced mortar/concrete cracking is experimentally investigated with optical frequency domain reflectometry (OFDR) distributed optical fiber sensors, and numerical simulation is performed with finite-element method (FEM). Mortar/concrete cylindrical specimens are instrumented with OFDR distributed optical fiber sensors and then subjected to accelerated corrosion tests till surface cracking. A total of 12 specimens are prepared and tested in consideration with three steel rebar sizes and four cover thicknesses. A localized corrosion model is proposed and incorporated into FEM to simulate mortar/concrete cover cracking and the evolution of OFDR fiber sensor strain with an increase of corrosion time. Experimental results show that strain peaks appear along the length of fiber sensors due to either localized corrosion of steel rebar or mortar/concrete cover cracking, and the initiation time of corrosion-induced mortar/concrete cracking is identified to be the time when the fiber sensor strain peak starts to increase rapidly. The cracking strain of mortar/concrete obtained based on OFDR fiber sensors is affected by environmental factors such as moisture level. Empirical equations are proposed to predict the critical penetration depth of steel rebar corrosion-induced mortar and concrete cracking, and the limitations for actual engineering applications are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a study on the suitability and accuracy of detecting structural cracks in brick masonry by exploiting the breakage of ordinary silica optical fibers bonded to its surface with an epoxy adhesive. The deformations and cracking of the masonry specimen, and the behavior of pilot optical signals transmitted through the fibers upon loading of the test specimen were observed. For the first time, reliable detection of structural cracks with a given minimum value was achieved, despite the random nature of the ultimate strength of the optical fibers. This was achieved using arrays of several optical fibers placed on the structural element. The detection of such cracks allows the degree of structural danger of buildings affected by earthquake or other destructive phenomena to be determined. The implementation of this technique is simple and cost effective. For this reason, it may have a broad application in permanent damage-detection systems in buildings in seismic zones. It may also find application in automatic systems for the detection of structural damage to the load-bearing elements of land vehicles, aircraft, and ships. [ABSTRACT FROM AUTHOR]

Since the optical signal is attenuated when it propagates forward, the uncertainty of the measurement at the end of the optical fiber is increased, which restricts the performance of the Raman Scattering Distributed Temperature Sensing System (RDTS). Therefore, it is essential to study the signal denoising method of the system. Existing signal denoising methods, such as wavelet transform, median filtering, singular value decomposition, 1DDCNN, etc., still have room for improvement in parameter adjustment, computational complexity, and denoising effect. Thus, we have proposed a novel deep-learning model called the down-sampling double network model (DSDN) for RDTS signal denoising with high performance based on down-sampling and convolutional neural network (CNN). The DSDN model includes a down-sampling part, a one-dimensional full convolution part, and a ResNet part. It uses synthetic data as a training dataset. We have designed model performance evaluation experiments based on synthetic data and real RDTS data under different noise intensities. The root mean square error (RMSE) of the RDTS signal after DSDN noise reduction has been reduced to 0.189 °C, which is better than 2.117 °C of wavelet, 2.077 °C of median filter, 0.968 °C of 1DDCNN model. The mean absolute error (MAE) has been reduced to 0.165 °C, which is better than 1.716 °C of the wavelet transform, 1.402 °C of median filter, 0.564 °C of 1DDCNN. And smooth has been reduced to 0.074, which is better than wavelet's 1.298, median filter's 1.171, and 1DDCNN's 0.149. The results show that the DSDN model proposed in this article has excellent signal denoising performance and good robustness on different noise intensities and can be applied to RDTS systems. [ABSTRACT FROM AUTHOR]

Pitting corrosion of steel bars can greatly impair mechanical properties of steel bars, so detecting pitting corrosion timely and accurately is crucial for assessing the health of structures. However, most current corrosion detection methods have some difficulties measuring pitting corrosion level of steel bars effectively. Considering that corrosion pits can cause strain redistribution of steel bar in the tensile state, this study proposes a method to quantitatively determine the pitting corrosion level through monitoring the steel strain distribution. Distributed optical fiber sensors (DOFS) based on Rayleigh scattering and capable of achieving the spatial resolution in millimeter scale were adopted to monitor the strain distributions of notched HRB400E steel bars subjected to tensile stress, and finite element (FE) method was employed to analyze the strain distributions of steel bars with different pit geometries. Experimental results showed that the bare fiber sensors (PI-FS) measured steel strain more accurately than jacketed fiber sensors. From strain distributions monitored by PI-FS, the pit location and pit length can be directly determined. Further, FE results revealed that the strain distribution along the fiber sensor position was significantly affected by the fiber sensor position relative to the pit mouth. Finally, the procedures to determine the pitting corrosion level from DOFS data and FE results were presented by mathematically comparing the similarity of strain curves given by the fiber sensor on a pitting-corroded bar and FE analyses of steel bars with different corrosion levels. In the end, the issues related to the practical applicability of the proposed method were discussed and limitations of this study were addressed. Although with limitations, this study provided a novel and promising way to quantitatively monitor the pitting corrosion level based on the strain distribution of steel bars. • New method to monitor pitting corrosion level by DOFS was proposed. • Position of fiber sensors relative to the pit mouth governed the strain distribution according to FEM. • Pitting corrosion quantification was achieved by matching strain distributions from DOFS and FEM. [ABSTRACT FROM AUTHOR]

A pattern recognition method for intrusion signals is introduced, leveraging distributed optical fiber sensors and convolutional neural networks. To enhance the model's generalization capabilities, two strategies are employed. Firstly, the sensor structure is refined, incorporating the strengths of both the Sagnac and Michelson interferometers to create a hybrid design with a wide frequency response. Comparative experiments confirm that this exceptional frequency response significantly boosts the model's generalization power. Secondly, to address the limitations of distributed fiber optic sensors, a multimodal approach is proposed, integrating video frame difference and fiber optic pattern recognition. The trained convolutional neural network model exhibits low computational overhead, robust generalization, and practical applicability. When applied to a dataset collected in diverse scenarios not included in the model training, the model achieved a CNR of 0% and a FPR of only 0.26% for the intrusion behavior of climbing fences. [ABSTRACT FROM AUTHOR]

Distributed fiber optic sensors (DFOS) can detect structural cracks and structural deformation with high accuracy and wide measurement range. This study monitors the segmental prestressed bent cap, assembled with a large key dry joint, based on optical fiber technology, and it allows the comparison of its damaging process with that of a monolithic cast in place counterpart. The obtained results, comprising cross-section strain distributions, longitudinal strain profiles, neutral axis location, crack pattern, and the damage process, show that the DFOS technology can be successfully used to analyze the complex working stress state of the segmental beam with shear key joints, both in the elastic range and at the ultimate load, and to successfully identify the changing characteristics of the stress state of the segmental capping beam model when elastic beam theory no longer applies. The DFOS data confirm that the shear key joint, as the weak point of the segmental cap beam, results in the high stress concentration area, and the damage rate is higher than that of the cast-in-place beam. The accurate monitoring by the DFOS allows for the realization that the damage occurs at the premature formation of a concentrated compression zone on the upper part of the shear key.

We live in an environment of ever-growing demand for transport networks, which also have ageing infrastructure. However, it is not feasible to replace all the infrastructural assets that have surpassed their service lives. The commonly established alternative is increasing their durability by means of Structural Health Monitoring (SHM)-based maintenance and serviceability. Amongst the multitude of approaches to SHM, the Digital Twin model is gaining increasing attention. This model is a digital reconstruction (the Digital Twin) of a real-life asset (the Physical Twin) that, in contrast to other digital models, is frequently and automatically updated using data sampled by a sensor network deployed on the latter. This tool can provide infrastructure managers with functionalities to monitor and optimize their asset stock and to make informed and data-based decisions, in the context of day-to-day operative conditions and after extreme events. These data not only include sensor data, but also include regularly revalidated structural reliability indices formulated on the grounds of the frequently updated Digital Twin model. The technology can be even pushed as far as performing structural behavioral predictions and automatically compensating for them. The present exploratory review covers the key Digital Twin aspects—its usefulness, modus operandi, application, etc.—and proves the suitability of Distributed Sensing as its network sensor component. [ABSTRACT FROM AUTHOR]

Optical frequency domain reflectometry (OFDR) is a kind of distributed optical fiber sensors (DOFS) which has attracted an increasing amount of research attention. The OFDR sensor has a high spatial resolution and large dynamic range, which makes it useful in a large amount of sensing scenarios. In this paper, we will provide a review of the recent advances in OFDR. We introduce the sensing principles and progress for performance improvement of the system. We also cover the applications of OFDR-based sensing system, including sensing of temperature, strain, vibration, pressure, magnetic field, refractive index, radiation, 3D-shape, gas, gas flow rate, and so on.

Glass fiber/epoxy (GF/E) composites are being extensively scaled-up as anti-corrosion materials in chemical industries because of the relatively low-cost, and are easy to manufacture. Nonetheless, Glass fiber/epoxy composites are not entirely immune to corrosion when exposed to dilute acidic solutions due to the reduction in mechanical strength caused by swelling, which adversely affects the structural integrity. Mathematical correlations quantifying the stress and mechanical property reduction with the time of exposure are a tool to design the service life. The composite structure has been monitored throughout its service life in the present study, by instrumenting the GF/E composite with distributed optical fiber sensors (DOFS). The instrumented composites along with test specimens are aged in aqueous 10 % sulphuric acid environment at room temperature to measure the mechanical properties and weight gain due to the transport of the acidic medium. The strain evolution with the time of exposure is recorded by processing the signals received from the DOFS. The experimental gravimetric data are fitted into the Langmuir model, and the model parameters such as diffusivity (D), β and γ are evaluated. Finally, mathematical correlations developed by quantifying the stress and reduction in mechanical properties with exposure time can be used to determine the mechanical health of GF/E composite structure exposed to sulphuric acid solutions. The changes in the microstructure of GF/E composites is also investigated using field emission-scanning electron microscope (FE-SEM). The technique of instrumenting the GF/E composites by embedding it in the composite structure during the fabrication process is also developed. [ABSTRACT FROM AUTHOR]

We have designed and fabricated a single-mode Raman gain fiber (RGF) and use it to experimentally demonstrate a Raman distributed temperature sensor (RDTS) for high-precision temperature measurement with low power consumption. We have performed simulation to analyze the impact of fluorine-doped inner cladding on the control of the acoustic field and suppression of stimulated Brillouin scattering (SBS), showing that the SBS threshold can be improved by 37dB at 6wt% fluorine-doping concentration. Taking advantage of high Raman gain, a maximum signal-to-noise ratio (SNR) improvement of 6dB has been realized by using RGF under the same pump power as by using single-mode fiber (SMF), and the temperature uncertainty at the fiber end is enhanced from 0.9°C to 0.5°C. To achieve comparable sensing accuracy as that of SMF-based RDTS, our RGF-based RDTS only consumes half of the power, showing good energy efficiency. The magnitude of SNR and temperature uncertainty enhancement is limited by the relatively large fiber attenuation, but it can be further improved through optimization of the fiber design with high fluorine-doping concentration and graded index structure. [ABSTRACT FROM AUTHOR]

In this paper, we propose and demonstrate a damage detection technique based on the automatic classification of the Lamb wave signals acquired on a metallic plate. In the reported experiments, Lamb waves are excited in an aluminum plate through a piezoelectric transducer glued onto the monitored structure. The response of the monitored structure is detected through a high-resolution phase-sensitive optical time-domain reflectometer (ϕ-OTDR). The presence and location of a small perturbation, induced by placing a lumped mass of 5 g on the plate, are determined by processing the optical fiber sensor data through support vector machine (SVM) classifiers trained with experimental data. The results show that the proposed method takes full advantage of the multipoint sensing nature of the ϕ-OTDR technology, resulting in accurate damage detection and localization.

• An extensible local-global network is proposed for sensor heterogeneity in physical intrusion monitoring based on DOFS for the first time. • A deep isolation forest (DIF) is proposed to improve performance of local classifiers in extremely imbalanced, large-scale and high-dimensional cases. • The semi-sharing strategy and parallel computing framework of proposed network are introduced to reduce the computation costs in training and monitoring. • The characteristics of the proposed method are detailedly discussed in theory, and the effectiveness is verified through real-field experiments. This paper proposes a local–global semi-sharing network (LGSSN) for heterogeneous signals in physical intrusion monitoring. The signals are collected by heterogeneous distributed optical fiber sensor (DOFS). The local classifier of LGSSN is constructed via a hybrid model deep isolation forest (DIF). It can extract the dominant representations of original high-dimensional signals through deep autoencoders (DAE). Then, an isolation forest (IF) is added to the last layer to obtain local classification for extremely imbalanced cases. In addition, the network is simplified by semi-sharing strategy, and a parallel computing framework is presented for accelerating the process. Further, the final decision on monitoring state is acquired by a Bayesian inference-based global integrated monitor (GIM) with enhanced classification accuracy. The proposed strategy is tested on a monitoring application along the Nanjing Metro Line S7, Jiangsu Province, China. Comparative experimental results illustrate the feasibility and effectiveness of proposed strategy. [ABSTRACT FROM AUTHOR]

The loop configuration consisting of a lead fiber and a sensing fiber is a common approach to realize Brillouin Optical Time-Domain Analysis (BOTDA), which is however impractical to implement for some field scenarios where only a single fiber is physically available. In this paper, a novel single-fiber-based BOTDA with far-end modulation is proposed and experimentally demonstrated, in which an auxiliary light and a pulse are injected from the near-end of the fiber, and the counter-propagating probe light is generated by modulating the auxiliary light from the far-end. By dedicatedly designing the frequency and temporal profile of each lightwave, Brillouin interaction takes place only between the pulse and the probe light, while stray effects such as four wave mixing and Rayleigh beating noise are avoided, which constitutes the key advantage of the propose technique with respect to traditional single-fiber-based BOTDA techniques. A 80-km-long sensing range, 1.73 MHz frequency accuracy and 2 m spatial resolution is experimentally demonstrated with 4000 trace averages. [ABSTRACT FROM AUTHOR]

This paper presents a study on the suitability and accuracy of detecting structural cracks in brick masonry by exploiting the breakage of ordinary silica optical fibers bonded to its surface with an epoxy adhesive. The deformations and cracking of the masonry specimen, and the behavior of pilot optical signals transmitted through the fibers upon loading of the test specimen were observed. For the first time, reliable detection of structural cracks with a given minimum value was achieved, despite the random nature of the ultimate strength of the optical fibers. This was achieved using arrays of several optical fibers placed on the structural element. The detection of such cracks allows the degree of structural danger of buildings affected by earthquake or other destructive phenomena to be determined. The implementation of this technique is simple and cost effective. For this reason, it may have a broad application in permanent damage-detection systems in buildings in seismic zones. It may also find application in automatic systems for the detection of structural damage to the load-bearing elements of land vehicles, aircraft, and ships.

Spatial resolution improvement from an acquired measurement using long pulse is developed for Brillouin optical time domain analysis (BOTDA) systems based on the total variation deconvolution algorithm. The frequency dependency of Brillouin gain temporal envelope is investigated by simulation, and its impact on the recovered results of deconvolution algorithm is thoroughly analyzed. To implement a reliable deconvolution process, differential pulse-width pair (DPP) technique is utilized to effectively eliminate the systematic Brillouin frequency shift (BFS) distortion stemming from the frequency dependency of temporal envelope. The width of the pulse pairs should be larger than 40 ns as is analyzed theoretically and verified experimentally. It has been demonstrated that the proposed method can realize flexible adjustment of spatial resolution with enhanced signal-to-noise ratio (SNR) from an established measurement with long pump pulse. In the experiment, the spatial resolution is increased to 0.5 m and 1 m with high measurement accuracy by using the deconvolution algorithm from the measurement of 60/40 ns DPP signals. Compared with the raw DPP results with the same spatial resolution, 7.9 dB and 5.9 dB SNR improvements are obtained for 0.5 m and 1 m spatial resolution respectively, thanks to the denoising capability of the total variation deconvolution algorithm. The impact of sampling rate on the recovery results is also studied. The proposed sensing system allows for distortion-free Brillouin distributed sensing with higher spatial resolution and enhanced SNR from the conventional DPP setup with long pulse pairs. [ABSTRACT FROM AUTHOR]

Brillouin optical time-domain analyzer (BOTDA) is used to monitor the temperature and strain along a fiber. So far, neural network and machine learning methods have been successfully applied for temperature extraction. But for different frequency scanning steps, different networks should be designed and trained. Here, a BOTDA assisted by kernel extreme learning machine (K-ELM) with high generalization is proposed and experimentally demonstrated. By utilizing K-ELM, the raw Brillouin gain spectra measured from BOTDA system are classified into different temperature classes. The performance of K-ELM is investigated both in simulation and experiment under different cases of signal-to-noise ratios, pump pulse widths, and frequency scanning steps. Compared with curve fitting methods, the K-ELM algorithm has better measurement accuracy of 0.3 °C and it realizes great improvement of the processing speed over 120 times. The ultrafast processing speed, high accuracy and generality make K-ELM become a highly competitive candidate for the high-speed BOTDA sensing system. [ABSTRACT FROM AUTHOR]

Raman-based distributed temperature sensing (RDTS) can achieve temperature measurement of tens of kilometers and is widely used in temperature monitoring of crucial facilities. The accuracy of RDTS is highly determined by the signal-to-noise ratio (SNR) of the acquired spontaneous Raman scattering (SpRS) signals, which is about 60 dB weaker than the pump pulse. Therefore, the performance of single-mode fiber (SMF) based conventional RDTS is poor. To improve its performance, many methods have been proposed, including the use of special optical fibers, pulse coding techniques, and denoising algorithms. However, these methods have their limitations. Here, we propose and experimentally demonstrate a deep 1-D denoising convolutional neural network (1DDCNN) to enhance the performance of RDTS. A simplified RDTS model is built to train and optimize the 1DDCNN. To verify the performance of the 1DDCNN on actual data, we experimentally measure the SpRS data of a 10-km SMF with an average time of 1 s and a spatial resolution of 3 m. The well-trained 1DDCNN reduces the temperature uncertainty from 6.4 °C to 0.7 °C with high fidelity. As a comparison, the commonly used wavelet denoising algorithm can only reduce it to 3.7 °C. Besides, the 1DDCNN does not require manual parameter adjustment and is not affected by the sampling rate, giving it significant advantages in practical applications compared with conventional denoising algorithms. Moreover, we believe that the proposed 1DDCNN can be applied to other distributed optical fiber sensing systems by fine-tuning the network with appropriate training data. [ABSTRACT FROM AUTHOR]

This paper investigates the use of distributed optical fiber sensors (DOFS) based on Optical Frequency Domain Reflectometry of Rayleigh backscattering for Structural Health Monitoring purposes in civil engineering structures. More specifically, the results of a series of laboratory experiments aimed at assessing the suitability and accuracy of DOFS for crack monitoring in reinforced concrete members subjected to external loading are reported. The experiments consisted on three-point bending tests of concrete beams, where a polyamide-coated optical fiber sensor was bonded directly onto the surface of an unaltered reinforcement bar and protected by a layer of silicone. The strain measurements obtained by the DOFS system exhibited an accuracy equivalent to that provided by traditional electrical foil gauges. Moreover, the analysis of the high spatial resolution strain profiles provided by the DOFS enabled the effective detection of crack formation. Furthermore, the comparison of the reinforcement strain profiles with measurements from a digital image correlation system revealed that determining the location of cracks and tracking the evolution of the crack width over time were both feasible, with most errors being below ±3 cm and ±20 µm, for the crack location and crack width, respectively. [ABSTRACT FROM AUTHOR]

The sensing applications nowadays are always more used for structural and engineering-geological applications. In this work, an experimental monitoring system of an underground marble quarry, located in the Apuan Alps (Tuscany, Italy) is presented. The system is composed by Distributed Optical Fiber Sensors (DOFS) based on Brillouin Frequency Shift (BFS). By using a control unit, multitemporal data of strain and temperature were measured thanks to the installation of 250 linear meters of DOFS placed around two pillars. Terrestrial Laser Scanning (TLS) surveys, aided by GNSS (Global Navigation Satellite System) and TS (Total Station) measurements, were executed with the aim of: i) identifying physically inaccessible rock joints (i.e. height of the pillars), ii) georeferencing the DOFS and, iii) locating any strain phenomenon. The integration of a DOFS monitoring system with geomatic technologies has given the possibility to initialize a real-time monitoring system aimed at protecting the safety of the workers from possible rocky wall collapses. The results obtained in this work are the texturized 3D model of the analyzed pillars, the DEM and the orthophoto of the quarry, and the profiles of BFS, strain and temperature variation. This research was funded by Tuscany Region (Italy) though the POR FESR 2014-2020 plan. [ABSTRACT FROM AUTHOR]

The present study investigates the environmental durability of a distributed optical fiber sensing (DOFS) cable on the market, commonly used for distributed strain measurements in reinforced concrete structures. An extensive experimental program was conducted on different types of specimens (including samples of bare DOFS cable and plain concrete specimens instrumented with this DOFS cable) that were exposed to accelerated and natural ageing (NA) conditions for different periods of up to 18 months. The instrumentation of both concrete specimens consisted of DOFS cables embedded at the center of the specimens and bonded at the concrete surface, as these two configurations are commonly deployed in the field. In these configurations, the alkalinity of the surrounding cement medium and the outdoor conditions are the main factors potentially affecting the characteristics of the DOFS component materials and the integrity of the various interfaces, and hence impacting the strain transfer process between the host structure and the core optical fiber (OF). Therefore, immersion in an alkaline solution at an elevated temperature or freeze/thaw (F/T) and immersion/drying (I/D) cycles were chosen as accelerated ageing conditions, depending on the considered configuration. Mechanical characterizations by tensile and pull-out tests were then carried out on the exposed specimens to assess the evolution of the mechanical properties of individual component materials as well as the evolution of bond properties at various interfaces (internal interfaces of the DOFS cable, and interface between the cable and the host structure) during ageing. Complementary physico-chemical characterizations were also performed to better understand the underlying degradation processes. The experimental results highlight that immersion in the alkaline solution induced a significant and rapid decrease in the bond properties at internal interfaces of the DOFS cable and at the cable/concrete interface (in the case of the embedded cable configuration), which was assigned to chemical degradation at the surface of the cable coating in contact with the solution (hydrolysis and thermal degradation of the EVA copolymer component). Meanwhile, F/T and I/D cycles showed more limited effects on the mechanical properties of the component materials and interfaces in the case of the bonded cable configuration. A comparison with the same specimens exposed to outdoor NA suggested that the chosen accelerated ageing conditions may not be totally representative of actual service conditions, but provided indications for improving the ageing protocols in future research. In the last part, an analysis of the distributed strain profiles collected during pull-out tests on instrumented concrete specimens clearly illustrated the consequences of ageing processes on the strain response of the DOFS cable.

We demonstrate the use of a graded-index perfluorinated optical fiber (GI-POF) for distributed static and dynamic strain measurements based on Rayleigh scattering. The system is based on an amplitude-based phase-sensitive Optical Time-Domain Reflectometry (ϕ-OTDR) configuration, operated at the unconventional wavelength of 850 nm. Static strain measurements have been carried out at a spatial resolution of 4 m and for a strain up to 3.5% by exploiting the increase of the backscatter Rayleigh coefficient consequent to the application of a tensile strain, while vibration/acoustic measurements have been demonstrated for a sampling frequency up to 833 Hz by exploiting the vibration-induced changes in the backscatter Rayleigh intensity time-domain traces arising from coherent interference within the pulse. The reported tests demonstrate that polymer optical fibers can be used for cost-effective multiparameter sensing.

This document showcases the latest research conducted within UPC–BarcelonaTech on the performance of distributed optical fiber sensors (DOFS), more specifically the case of the optical backscattered reflectometry (OBR) system, in the structural health monitoring (SHM) of bridges, and large scale structures. This technology has demonstrated promising results for monitoring applications in a wide range of fields but due to its novelty, still presents several uncertainties which prevent its use in a more systematic and efficient way in civil engineering infrastructures, being this even more evident in the case of concrete structures. Therefore, different laboratory experimental campaigns were devised where multiple aspects of the instrumentation of DOFS technology in civil engineering applications were assessed and scrutinized. Such as the study of new implementation methods, comparison, and performance analysis of different bonding adhesives and spatial resolution. Additionally, the fatigue performance of this sensing typology was also assessed. Furthermore, the use of the OBR system technology was applied in a real world structure in Barcelona, Spain, where new challenging conditions had to be addressed. Consequently, with this work, different conclusions are obtained related to the proficiency and limitations on the use of this particular type of optical sensing system in concrete structures.

Optical Frequency Domain Reflectometry (OFDR) is used to make temperature distributed sensing measurements along a fiber by exploiting Rayleigh backscattering. This technique presents high spatial and high temperature resolutions on temperature ranges of several hundred of degrees Celsius. With standard telecommunications fibers, measurement errors coming from the correlation between a high temperature Rayleigh trace and the one taken as a reference at room temperature could be present at extremely high temperatures. These correlation errors, due to low backscattering signal amplitude and unstable backscattering signal, induce temperature measurement errors. Thus, for high temperature measurement ranges and at extremely high temperatures (e.g., at 800 °C), a known solution is to use fibers with femtosecond laser inscribed nanograting. These fs-laser-insolated fibers have a high amplitude and thermally stable scattering signal, and they exhibit lower correlation errors. In this article, temperature sensing at 800 °C is reported by using an annealed zirconia-doped optical fiber with an initial 40.5-dB enhanced scattering signal. The zirconia-doped fiber presents initially OFDR losses of 2.8 dB/m and low OFDR signal drift at 800 °C. The ZrO2-doped fiber is an alternative to nanograting-inscribed fiber to make OFDR distributed fiber sensing on several meters with gauge lengths of 1 cm at high temperatures.

The present work is a comprehensive collection of recently published research articles on Structural Health Monitoring (SHM) campaigns performed by means of Distributed Optical Fiber Sensors (DOFS). The latter are cutting-edge strain, temperature and vibration monitoring tools with a large potential pool, namely their minimal intrusiveness, accuracy, ease of deployment and more. Its most state-of-the-art feature, though, is the ability to perform measurements with very small spatial resolutions (as small as 0.63 mm). This review article intends to introduce, inform and advise the readers on various DOFS deployment methodologies for the assessment of the residual ability of a structure to continue serving its intended purpose. By collecting in a single place these recent efforts, advancements and findings, the authors intend to contribute to the goal of collective growth towards an efficient SHM. The current work is structured in a manner that allows for the single consultation of any specific DOFS application field, i.e., laboratory experimentation, the built environment (bridges, buildings, roads, etc.), geotechnical constructions, tunnels, pipelines and wind turbines. Beforehand, a brief section was constructed around the recent progress on the study of the strain transfer mechanisms occurring in the multi-layered sensing system inherent to any DOFS deployment (different kinds of fiber claddings, coatings and bonding adhesives). Finally, a section is also dedicated to ideas and concepts for those novel DOFS applications which may very well represent the future of SHM.

The spatio-temporal evolution of the temperature induced over carbon fiber reinforced polymer (CFRP) laminates during drilling is monitored in real-time using a distributed optical fiber sensor based on optical frequency-domain reflectometry (OFDR). The proposed distributed measurement technique enables the simultaneous monitoring of thousands independent points on a CFRP plate during machining, being of special interest to measure the internal temperature of a workpiece. Experimental results validate the use of distributed OFDR-based sensing for this novel application, demonstrating a precise reconstruction of the two-dimensional (2D) temperature profile around the drilled hole, with a 2 mm spatial resolution and a sampling rate of 23.8 Hz (corresponding to a measurement interval of 42 ms). The high spatial and temporal resolutions provided by OFDR sensing offer unique features for this application, allowing for an accurate identification of the temporal evolution and spatial distribution of the 2D temperature profile originated during drilling. By embedding the sensing optical fiber in the interface between CFRP laminates and metals, a full map of the internal (interlayer) temperature of the CFRP plate can be obtained, demonstrating a feature that cannot be obtained by any other sensing technology. The proposed method can constitute a relevant tool for the identification of potential high temperatures occurring during machining, which could affect the quality of the borehole, induce material defects, and compromise the safety of an entire composite structure in service. [ABSTRACT FROM AUTHOR]

In order to both adjust the spatial resolution (SR) and narrow the Brillouin gain spectrum (BGS) linewidth in Brillouin optical time domain analysis system, a novel scheme based on differential pulse pair technique is proposed. By designing the phase and amplitude of the pulse properly, the higher peak gain and narrower linewidth of BGS are achieved compared to the conventional single pulse scheme with same SR. The pulse parameters for different SR are analytically solved and the performances of the sensor are theoretically and experimentally studied. Experimental results show that the linewidth of BGS is narrowed to 19 and 22 MHz in the case of 2 m SR and 1 m SR, which indicates 2.3 times and 4.3  times frequency accuracy improvements are achieved, respectively. Furthermore, the advantages of our proposal for small Brillouin frequency shift change are also investigated. [ABSTRACT FROM AUTHOR]

In this letter, we demonstrate a simple technique aimed to enhance the accuracy in dark-pulse Brillouin optical time-domain analysis (BOTDA) sensors. Modeling the stimulated Brillouin scattering in the frequency domain, we show that the degrading features related to the pump background can be removed by applying a high-pass filter to the raw data, at the cost of some degradation of the signal-to-noise ratio. A numerical analysis, as well as experimental tests carried out at 20-cm spatial resolution, validate the proposed technique. [ABSTRACT FROM AUTHOR]

A smart structure based on carbon fiber reinforced polymer (CFRP) embedding optical fibers is proposed for distributed sensing in structural health monitoring. The proposed CFRP package provides mechanical protection to the optical fiber, enables temperature-strain discrimination, and also facilitates the sensor's installation to secure reliable measurements. Experimental results verify a linear strain sensor response with temperature compensation, agreeing well with the response of strain gauges and the expected theoretical behavior. The smart structure can be used by gluing it on the surface of the monitored structure or by embedding it as one of the layers used during manufacturing big composite structures. [ABSTRACT FROM AUTHOR]

In recent years, many conventional image denoising techniques have been intensively studied to enhance the signal to noise ratio (SNR) of Brillouin optical time domain analyzer (BOTDA), due to their superior denoising performance to one-dimensional methods. However, in the case of low sampling rate, the details of the signal are smoothed out due to less useful information, resulting in a degradation of the spatial resolution. Moreover, these conventional denoising algorithms are quite time-consuming compared with the BOTDA measuring time. To overcome these drawbacks, we employ a feed-forward convolutional neural networks (CNN) based image denoising for BOTDA. A conventional BOTDA system with 15 ns pulse width is implemented to demonstrate the effectiveness of the exploited CNN-based denoising method. The actual electrical noise signals of the BOTDA at different sampling rates are collected to synthesize training samples. The CNN model is trained with the noise and simulated BOTDA signals. Experimental results show that SNR improvement of 13.43 dB, 13.57 dB, and 12.9 dB is achieved at a sampling rate of 500 MSa/s, 250 MSa/s, and 125 MSa/s, respectively, via the trained CNN denoiser. No spatial resolution distortion can be observed in the denoised BOTDA signals. Besides, the CNN denoiser only takes 0.045 s to process a 151 × 50000 image benefiting from GPU computing. This processing time is negligible compared with the acquisition time of BOTDA, which makes real-time denoising possible. [ABSTRACT FROM AUTHOR]

The non-linear interaction between a Rayleigh-backscattered wave and a forward-traveling optical pump pulse is explored using sources separated by approximately one Brillouin shift. It is shown that the pump pulse modulates the Rayleigh backscatter at those locations where the frequencies of the counter-propagating waves differ by a Brillouin shift. As a result, a new Brillouin optical time-domain analysis technique is demonstrated that measures the spatial distribution of the Brillouin gain spectrum from one end only of the sensing fiber. In our experiments, spectra were acquired at a rate of 40 spectra per second over a sensing range of order 1 km with a spatial resolution of 3 m. The experimental arrangement and data analysis are described and a dataset is processed to extract the real part of the Brillouin gain spectrum and determine the peak of the gain spectrum as a function of location along the fiber. We also show that the new technique detects local changes in the phase due to the Brillouin interaction. The potential and limitations of the new technique are also discussed. [ABSTRACT FROM AUTHOR]

Present research on strain transfer in optical fiber sensors focuses on high-precision, point-bonded fiber Bragg grating sensors. The spatial resolution of a traditional distributed fiber optic sensor (DOFS) reaches submeter or meter, and strain transfer in these sensors is rarely noticed. The accuracy of the DOFS based on optical frequency domain reflectometry used in our paper is improved significantly compared to previous sensors. It has an accuracy of 0.1 and a spatial resolution of 1 mm. Therefore, the strain transfer performance of such a high-precision DOFS should be investigated further. We fixed a DOFS on a host structure using an adhesive, and the factors influencing strain transfer were studied, including the "endpoint effect," bond length, shear modulus of the coating and adhesive layers, and thickness of the adhesive layer. A theoretical strain transfer model for a DOFS was designed and the theoretical strain transfer coefficient was calculated using numerical simulations. Furthermore, an evaluation of the theoretical model was implemented using a uniform strength beam. The experimental results are consistent with the simplified two-layer strain transfer model presented in our paper. The effect of the bond length on strain transfer is summarized from experimental and numerical simulation results, i.e., a larger adhesive length leads to a higher strain transfer coefficient and smaller "endpoint effect." If the shear modulus of the fiber coating layer and the glue is high, we obtain a high train transfer coefficient and small "endpoint effect." These conclusions provide a useful reference for the application of DOFS in practice. [ABSTRACT FROM AUTHOR]

Brillouin optical correlation-domain technologies are reviewed as "fiber optic nerve systems" for the health monitoring of large structures such as buildings, bridges, and aircraft bodies. The Brillouin scattering property is used as a sensing mechanism for strain and/or temperature. Continuous lightwaves are used in the technologies, and their optical coherence properties are synthesized to realize position-selective measurement. This coherence manipulation technology is called the "synthesis of optical coherence function (SOCF)". By utilizing SOCF technologies, stimulated Brillouin scattering is generated position-selectively along the fiber, which is named "Brillouin optical correlation domain analysis (BOCDA)". Spontaneous Brillouin scattering, which takes place at any portion along the fiber, can also be measured position-selectively by the SOCF technology. This is called "Brillouin optical correlation domain reflectometry (BOCDR)". When we use pulsed lightwaves that have the position information, sensing performances, such as the spatial resolution, are inherently restricted due to the Brillouin scattering nature. However, in the correlation-domain technologies, such difficulties can be reduced. Superior performances have been demonstrated as distribution-sensing mechanisms, such as a 1.6-mm high spatial resolution, a fast measurement speed of 5000 points/s, and a 7000-με strain dynamic range, individually. The total performance of the technologies is also discussed in this paper. A significant feature of the technologies is their random accessibility to discrete multiple points that are selected arbitrarily along the fiber, which is not realized by the time domain pulsed-lightwave technologies. Discriminative and distributed strain/temperature measurements have also been realized using both the BOCDA technology and Brillouin dynamic grating (BDG) phenomenon, which are associated with the stimulated Brillouin scattering process. In this paper, the principles, functions, and applications of the SOCF, BOCDA, BOCDR, and BDG-BOCDA systems are reviewed, and their historical aspects are also discussed. [ABSTRACT FROM AUTHOR]