Recent Progress of Fiber-Optic Sensors for the Structural Health Monitoring of Civil Infrastructure

Multilayer Structure Damage Detection Using Optical Fiber Acoustic Sensing and Machine Learning

Over the past decade, distributed acoustic sensing has been utilized for structural health monitoring in various applications, owing to its continuous measurement capability in both time and space and its ability to deliver extensive data on the conditions of large structures using just a single optical cable. This work aims to evaluate the performance of distributed acoustic sensing for monitoring a multilayer structure on a laboratory scale. The proposed structure comprises four layers: a medium-density fiberboard and three rigid polyurethane foam slabs. Three different damages were emulated in the structure: two in the first layer of rigid polyurethane foam and another in the medium-density fiberboard layer. The results include the detection of the mechanical wave, comparing the response with point sensors used for reference, and evaluating how the measured signal behaves in time and frequency in the face of different damages in the multilayer structure. The tests demonstrate that evaluating signals in both time and frequency domains presents different characteristics for each condition analyzed. The supervised support vector machine classifier was used to automate the classification of these damages, achieving an accuracy of 93%. The combination of distributed acoustic sensing with this learning algorithm creates the condition for developing a smart tool for monitoring multilayer structures.

Direct detection Φ-OTDR based on UWFBG array using linear-phase-modulated double-pulse

We propose what we believe to be a novel direct detection phase-sensitive optical time-domain reflectometry (Φ-OTDR) based on ultra-weak fiber Bragg grating (UWFBG) array to achieve distributed vibration measurements with exceptional sensitivity and remarkable stability. Our system employs a pulse modulator to generate a double pulse and achieves linear phase modulation of one pulse by one cycle through a phase modulator. The phase change can be quantitatively demodulated using our proposed N-step phase-shifted demodulation algorithm. This method effectively mitigates the influence of phase noise of the laser and the pulse modulator, while also eliminating fluctuations in the half-voltage of the phase modulator. Compared with the existing phase modulation methods, our method avoids stringent requirements for the stability and precision of phase modulation. Moreover, we propose a phase-shifted approximation method, breaking the limitation of sensing length on the traditional differential approximation method and improving the accuracy significantly. The technique's effectiveness is experimentally demonstrated on a 1 km UWFBG array with a reflectivity of -40 dB to -45 dB and a spatial resolution of 10 m. Vibrations with different amplitudes are measured quantitatively with good linearity. The low-frequency self-noise is greatly suppressed and the overall self-noise is -54.3 dB rad2/Hz.

A Deep Learning Approach for Autonomous Compression Damage Identification in Fiber-Reinforced Concrete Using Piezoelectric Lead Zirconate Titanate Transducers

Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open research challenge. This study proposes a new approach utilizing a 1-D convolution neural network to identify the formation of cracks from the raw electromechanical impedance (EMI) signature of externally bonded piezoelectric lead zirconate titanate (PZT) transducers. Externally bonded PZT transducers were used to determine the EMI signature of fiber-reinforced concrete specimens subjected to monotonous and repeatable compression loading. A leave-one-specimen-out cross-validation scenario was adopted for the proposed SHM approach for a stricter and more realistic validation procedure. The experimental study and the obtained results clearly demonstrate the capacity of the introduced approach to provide autonomous and reliable damage identification in a PZT-enabled SHM system, with a mean accuracy of 95.24% and a standard deviation of 5.64%.

Evaluation of Concrete Carbonation Based on a Fiber Bragg Grating Sensor

The carbonation of concrete greatly affects its service life. In this paper, fiber Bragg grating (FBG) sensors were used to investigate the relationship between concrete carbonation and its mechanical properties. A T130 High Sensitivity Strain Cable Sensor with a good linearity was used to monitor the internal strain in concrete, to investigate the variation in the elastic modulus of concrete with carbonation time. A mathematical model of elastic modulus and carbonation time of concrete based on FBG was established. At the same time, the authors explored the relationship between the carbonation depth and compressive strength of concrete and the carbonation time using a phenolphthalein solution test and a compressive strength test, respectively. The experimental results indicate that the carbonation depth, compressive strength, and elastic modulus of concrete increase with carbonation time. In the early stage of carbonation, these three parameters increase rapidly, while they grow slowly in the later stage of carbonation. The varying trend of the elastic modulus of concrete is consistent with the compressive strength, which shows a binomial relationship. Therefore, the elastic modulus, measured using FBG sensors, is used as an indicator of the characterization of the carbonation resistance of concrete. This work provides a new approach for concrete carbonation detection and assessment.

On-chip silicon electro-optical modulator with ultra-high extinction ratio for fiber-optic distributed acoustic sensing

Ultra-high extinction ratio (ER) optical modulation is crucial for achieving high-performance fiber-optic distributed acoustic sensing (DAS) for various applications. Bulky acousto-optical modulators (AOM) as one of the key devices in DAS have been used for many years, but their relatively large volume and high power consumption are becoming the bottlenecks to hinder the development of ultra-compact and energy-efficient DAS systems that are highly demanded in practice. Here, an on-chip silicon electro-optical modulator (EOM) based on multiple coupled microrings is demonstrated with ultra-high ER of up to 68 dB while the device size and power consumption are only 260 × 185 μm2 and 3.6 mW, respectively, which are at least two orders of magnitude lower than those of a typical AOM. Such an on-chip EOM is successfully applied to DAS with an ultra-high sensitivity of -71.2 dB rad2/Hz (4 pε/√Hz) and a low spatial crosstalk noise of -68.1 dB rad2/Hz, which are very similar to those using an AOM. This work may pave the way for realization of next-generation ultra-compact DAS systems by integration of on-chip opto-electronic devices and modules with the capability of mass-production.

A Review of Approaches for Mitigating Effects from Variable Operational Environments on Piezoelectric Transducers for Long-Term Structural Health Monitoring

Extending the service life of ageing infrastructure, transportation structures, and processing and manufacturing plants in an era of limited resources has spurred extensive research and development in structural health monitoring systems and their integration. Even though piezoelectric transducers are not the only sensor technology for SHM, they are widely used for data acquisition from, e.g., wave-based or vibrational non-destructive test methods such as ultrasonic guided waves, acoustic emission, electromechanical impedance, vibration monitoring or modal analysis, but also provide electric power via local energy harvesting for equipment operation. Operational environments include mechanical loads, e.g., stress induced deformations and vibrations, but also stochastic events, such as impact of foreign objects, temperature and humidity changes (e.g., daily and seasonal or process-dependent), and electromagnetic interference. All operator actions, correct or erroneous, as well as unintentional interference by unauthorized people, vandalism, or even cyber-attacks, may affect the performance of the transducers. In nuclear power plants, as well as in aerospace, structures and health monitoring systems are exposed to high-energy electromagnetic or particle radiation or (micro-)meteorite impact. Even if environmental effects are not detrimental for the transducers, they may induce large amounts of non-relevant signals, i.e., coming from sources not related to changes in structural integrity. Selected issues discussed comprise the durability of piezoelectric transducers, and of their coupling and mounting, but also detection and elimination of non-relevant signals and signal de-noising. For long-term service, developing concepts for maintenance and repair, or designing robust or redundant SHM systems, are of importance for the reliable long-term operation of transducers for structural health monitoring.

Fiber Optic-Based Durability Monitoring in Smart Concrete: A State-of-Art Review

Concrete is the most commonly used construction material nowadays. With emerging cutting-edge technologies such as nanomaterials (graphene, carbon nanotubes, etc.), advanced sensing (fiber optics, computer tomography, etc.), and artificial intelligence, concrete can now achieve self-sensing, self-healing, and ultrahigh performance. The concept and functions of smart concrete have thus been partially realized. However, due to the wider application location (coastal areas, cold regions, offshore, and deep ocean scenarios) and changing climate (temperature increase, more CO2 emissions, higher moisture, etc.), durability monitoring (pH, ion penetration, carbonation, corrosion, etc.) becomes an essential component for smart concrete. Fiber optic sensors (FOS) have been widely explored in recent years for concrete durability monitoring due to their advantages of high sensitivity, immunity to harsh environments, small size, and superior sensitivity. The purpose of this review is to summarize FOS development and its application in concrete durability monitoring in recent years. The objectives of this study are to (1) introduce the working principle of FOS, including fiber Bragg grating (FBG), long-period fiber grating (LPFG), surface plasmon resonance (SPR), fluorescence-based sensors, and distributed fiber optic sensors (DFOS); (2) compare the sensitivity, resolution, and application scenarios of each sensor; and (3) discuss the advantages and disadvantages of FOS in concrete durability monitoring. This review is expected to promote technical development and provide potential research paths in the future for FOS in durability monitoring in smart concrete.

Hybrid Distributed Optical Fiber Sensor for the Multi-Parameter Measurements

Distributed optical fiber sensors (DOFSs) are a promising technology for their unique advantage of long-distance distributed measurements in industrial applications. In recent years, modern industrial monitoring has called for comprehensive multi-parameter measurements to accurately identify fault events. The hybrid DOFS technology, which combines the Rayleigh, Brillouin, and Raman scattering mechanisms and integrates multiple DOFS systems in a single configuration, has attracted growing attention and has been developed rapidly. Compared to a single DOFS system, the multi-parameter measurements based on hybrid DOFS offer multidimensional valuable information to prevent misjudgments and false alarms. The highly integrated sensing structure enables more efficient and cost-effective monitoring in engineering. This review highlights the latest progress of the hybrid DOFS technology for multi-parameter measurements. The basic principles of the light-scattering-based DOFSs are initially introduced, and then the methods and sensing performances of various techniques are successively described. The challenges and prospects of the hybrid DOFS technology are discussed in the end, aiming to pave the way for a vaster range of applications.

Machine Learning Approaches in Brillouin Distributed Fiber Optic Sensors

This paper presents reported machine learning approaches in the field of Brillouin distributed fiber optic sensors (DFOSs). The increasing popularity of Brillouin DFOSs stems from their capability to continuously monitor temperature and strain along kilometer-long optical fibers, rendering them attractive for industrial applications, such as the structural health monitoring of large civil infrastructures and pipelines. In recent years, machine learning has been integrated into the Brillouin DFOS signal processing, resulting in fast and enhanced temperature, strain, and humidity measurements without increasing the system's cost. Machine learning has also contributed to enhanced spatial resolution in Brillouin optical time domain analysis (BOTDA) systems and shorter measurement times in Brillouin optical frequency domain analysis (BOFDA) systems. This paper provides an overview of the applied machine learning methodologies in Brillouin DFOSs, as well as future perspectives in this area.

Composite Bridge Girders Structure Health Monitoring Based on the Distributed Fiber Sensing Textile

Distributed structure health monitoring has been a hot research topic in recent years, and optic fiber sensors are largely developed for the advantages of high sensitivity, better spatial resolution, and small sensor size. However, the limitation of fibers in installation and reliability has become one of the major drawbacks of this technology. This paper presents a fiber optic sensing textile and a new installation method inside bridge girders to address those shortcomings in fiber sensing systems. The sensing textile was utilized to monitor strain distribution in the Grist Mill Bridge located in Maine based on Brillouin Optical Time Domain Analysis (BOTDA). A modified slider was developed to increase the efficiency of installation in the confined bridge girders. The bridge girder's strain response was successfully recorded by the sensing textile during the loading tests that involved four trucks on the bridge. The sensing textile demonstrated the capability to differentiate separated loading locations. These results demonstrate a new way of installing fiber optic sensors and the potential applications of fiber optic sensing textiles in structural health monitoring.

Young's Modulus-Independent Determination of Fibre Parameters for Rayleigh-Based Optical Frequency Domain Reflectometry from Cryogenic Temperatures up to 353 K

The magnetic spectrometer AMS-100, which includes a superconducting coil, is designed to measure cosmic rays and detect cosmic antimatter in space. This extreme environment requires a suitable sensing solution to monitor critical changes in the structure such as the beginning of a quench in the superconducting coil. Rayleigh-scattering-based distributed optical fibre sensors (DOFS) fulfil the high requirements for these extreme conditions but require precise calibration of the temperature and strain coefficients of the optical fibre. Therefore, the fibre-dependent strain and temperature coefficients KT and Kϵ for the temperature range from 77 K to 353 K were investigated in this study. The fibre was integrated into an aluminium tensile test sample with well-calibrated strain gauges to determine the fibre's Kϵ independently of its Young's modulus. Simulations were used to validate that the strain caused by changes in temperature or mechanical conditions was the same in the optical fibre as in the aluminium test sample. The results indicated a linear temperature dependence of Kϵ and a non-linear temperature dependence of KT. With the parameters presented in this work, it was possible to accurately determine the strain or temperature of an aluminium structure over the entire temperature range from 77 K to 353 K using the DOFS.

Fiber Optic Sensing Technology and Vision Sensing Technology for Structural Health Monitoring

Structural health monitoring is currently a crucial measure for the analysis of structural safety. As a structural asset management approach, it can provide a cost-effective measure and has been used successfully in a variety of structures. In recent years, the development of fiber optic sensing technology and vision sensing technology has led to further advances in structural health monitoring. This paper focuses on the basic principles, recent advances, and current status of applications of these two sensing technologies. It provides the reader with a broad review of the literature. It introduces the advantages, limitations, and future directions of these two sensing technologies. In addition, the main contribution of this paper is that the integration of fiber optic sensing technology and vision sensing technology is discussed. This paper demonstrates the feasibility and application potential of this integration by citing numerous examples. The conclusions show that this new integrated sensing technology can effectively utilize the advantages of both fields.

Laser Welding of Fiber and Quartz Glass Ferrule

Optical fiber sensors fabricated by bonding have several limitations. To address these limitations, a CO₂ laser welding process for an optical fiber and quartz glass ferrule is proposed in this study. A deep penetration welding method with optimal penetration (penetrating the base material only) is presented to weld a workpiece according to the requirements of the optical fiber light transmission, size characteristics of the optical fiber, and the keyhole effect of the deep penetration laser welding. Moreover, the influence of laser action time on the keyhole penetration is studied. Finally, laser welding is performed with a frequency of 24 kHz, power of 60 W, and duty cycle of 80% for 0.9 s. Subsequently, the optical fiber is subjected to out-of-focus annealing (0.83 mm, 20% duty cycle). The results show that deep penetration welding produces a perfect welding spot and has good quality; the hole generated from deep penetration welding has a smooth surface; the fiber can bear a maximum tensile force of 1.766 N. The performance of the optical fiber sensor is stable, and the maximum pressure deviation corresponding to the cavity length fluctuation is about 7.2 Pa. Additionally, the linear correlation coefficient R of the sensor is 0.99998.

A Systematic Review of Optimization Algorithms for Structural Health Monitoring and Optimal Sensor Placement

In recent decades, structural health monitoring (SHM) has gained increased importance for ensuring the sustainability and serviceability of large and complex structures. To design an SHM system that delivers optimal monitoring outcomes, engineers must make decisions on numerous system specifications, including the sensor types, numbers, and placements, as well as data transfer, storage, and data analysis techniques. Optimization algorithms are employed to optimize the system settings, such as the sensor configuration, that significantly impact the quality and information density of the captured data and, hence, the system performance. Optimal sensor placement (OSP) is defined as the placement of sensors that results in the least amount of monitoring cost while meeting predefined performance requirements. An optimization algorithm generally finds the "best available" values of an objective function, given a specific input (or domain). Various optimization algorithms, from random search to heuristic algorithms, have been developed by researchers for different SHM purposes, including OSP. This paper comprehensively reviews the most recent optimization algorithms for SHM and OSP. The article focuses on the following: (I) the definition of SHM and all its components, including sensor systems and damage detection methods, (II) the problem formulation of OSP and all current methods, (III) the introduction of optimization algorithms and their types, and (IV) how various existing optimization methodologies can be applied to SHM systems and OSP methods. Our comprehensive comparative review revealed that applying optimization algorithms in SHM systems, including their use for OSP, to derive an optimal solution, has become increasingly common and has resulted in the development of sophisticated methods tailored to SHM. This article also demonstrates that these sophisticated methods, using artificial intelligence (AI), are highly accurate and fast at solving complex problems.

Fabrication of High-Sensitivity Optical Fiber Sensor by an Improved Arc-Discharge Heating System

We proposed a high-sensitivity optical fiber sensor based on a dual-resonance helical long-period fiber grating (HLPG). The grating is fabricated in a single-mode fiber (SMF) by using an improved arc-discharge heating system. The transmission spectra and the dual-resonance characteristics of the SMF-HLPG near the dispersion turning point (DTP) were studied through simulation. In the experiment, a four-electrode arc-discharge heating system was developed. The system can keep the surface temperature of optical fiber relatively constant during the grating preparation process, which shows an advantage in preparing high-quality triple- and single-helix HLPGs. In particular, benefiting from this manufacturing system, the SMF-HLPG operating near the DTP was successfully prepared directly by arc-discharge technology, without secondary processing of the grating. As a typical application example of the proposed SMF-HLPG, physical parameters such as temperature, torsion, curvature and strain can be measured with high sensitivity by monitoring the variation of the wavelength separation in the transmission spectrum. Therefore, the proposed sensor and its fabrication technology have potential application prospects in practical sensing measurement.

Measurement of Gradient Strain Fields with Fiber-Optic Sensors

The results of measuring gradient strain fields by embedded or mounted point fiber-optic sensors based on Bragg gratings and distributed fiber-optic sensors based on Rayleigh scattering are discussed. Along with the experiment, the results of numerical modeling of strain measurement errors associated with the assumption of uniaxial stress state in the area of the embedded Bragg grating and measurement errors by distributed fiber-optic sensors associated with gage length are presented. Experimental results are presented for 3D printed samples and samples made of polymer composite material. The geometry of the samples was chosen based on the results of numerical simulations, and provides different variants of non-uniform strain distribution under uniaxial tension, including the variant in which the derivative of the strain distribution function changes its sign. A good agreement of numerical results and experimental data obtained by distributed and point fiber-optic sensors in areas where the derivative of the strain distribution function keeps a sign and an increase in the error of strain measurement results by distributed fiber-optic sensors in areas where this derivative changes sign are demonstrated.

Operational and Analytical Modal Analysis of a Bridge Using Low-Cost Wireless Arduino-Based Accelerometers

Arduino-based accelerometers are receiving wide attention from researchers to make long-term Structural Health Monitoring (SHM) feasible for structures with a low SHM budget. The current low-cost solutions found in the literature share some of the following drawbacks: (1) high noise density, (2) lack of wireless synchronization, (3) lack of automatic data acquisition and data management, and (4) lack of dedicated field tests aiming to compare mode shapes from Operational Modal Analysis (OMA) with those of a digital model. To solve these problems, a recently built short-span footbridge in Barcelona is instrumented using four Low-cost Adaptable Reliable Accelerometers (LARA). In this study, the automatization of the data acquisition and management of these low-cost solutions is studied for the first time in the literature. In addition, a digital model of the bridge under study is generated in SAP2000 using the available drawings and reported characteristics of its materials. The OMA of the bridge is calculated using Frequency Domain Decomposition (FDD) and Covariance Stochastic Subspace Identification (SSI-cov) methods. Using the Modal Assurance Criterion (MAC), the mode shapes of OMA are compared with those of the digital model. Finally, the acquired eigenfrequencies of the bridge obtained with a high-precision commercial sensor (HI-INC) showed a good agreement with those obtained with LARA.

Optical Fiber Sensors and Sensing Networks: Overview of the Main Principles and Applications

Optical fiber sensors present several advantages in relation to other types of sensors. These advantages are essentially related to the optical fiber properties, i.e., small, lightweight, resistant to high temperatures and pressure, electromagnetically passive, among others. Sensing is achieved by exploring the properties of light to obtain measurements of parameters, such as temperature, strain, or angular velocity. In addition, optical fiber sensors can be used to form an Optical Fiber Sensing Network (OFSN) allowing manufacturers to create versatile monitoring solutions with several applications, e.g., periodic monitoring along extensive distances (kilometers), in extreme or hazardous environments, inside structures and engines, in clothes, and for health monitoring and assistance. Most of the literature available on this subject focuses on a specific field of optical sensing applications and details their principles of operation. This paper presents a more broad overview, providing the reader with a literature review that describes the main principles of optical sensing and highlights the versatility, advantages, and different real-world applications of optical sensing. Moreover, it includes an overview and discussion of a less common architecture, where optical sensing and Wireless Sensor Networks (WSNs) are integrated to harness the benefits of both worlds.

Cylindrical Bidirectional Strain Sensors Based on Fiber Bragg Grating

To realize continuous real-time monitoring of the large-scale internal strain field of coal and rock mass, a bidirectional strain sensor based on FBGs encapsulated using a hollow cylindrical steel tube was designed. The sensor's structural parameters were optimized through unidirectional loading, and the strain change laws of the sensor were analyzed under unidirectional and bidirectional loading conditions, in which the stress-strain fitting curves of the sensor and the relationships of the strain in the vertical and horizontal directions were obtained under different lateral pressure loading conditions. A similar theoretical model was established to verify the accuracy of the linear relationship between the surrounding rock stress and the strain measured by the sensor system.

Hybrid B-OTDR/Φ-OTDR for multi-parameter measurement from a single end of fiber

The multi-parameter sensing is in great demand for comprehensive recognition in various application scenarios. We demonstrate a distributed optical fiber sensor (DOFS) for simultaneous vibration and temperature/strain sensing based on the integration of Brillouin optical time-domain reflectometry (BOTDR) and phase-sensitive optical time-domain reflectometry (Φ-OTDR). A double heterodyne detection configuration is set up to receive the Rayleigh scattering and Brillouin scattering simultaneously, which can enhance the signal-to-noise ratio (SNR) and reduce the polarization fading noise for the Brillouin signal at the same time. Most components in the setup are multiplexed for the Brillouin and Rayleigh signals. The overall cost is much lower than the summation of the BOTDR and the Φ-OTDR setup. In experiments, the setup is capable of measuring temperature change near the end of the 49.9 km long fiber with 0.381 MHz measurement uncertainty and restore different vibration patterns correctly by demodulating the phase variation of Rayleigh scattering signal, owning a 20 m spatial resolution. The sampling rate of the vibration measurement is 1.8 kHz, and the achieved dynamic strain resolution is 1.235 nɛ/√Hz with 100 Hz vibration.

Low-Cost Wireless Structural Health Monitoring of Bridges

Nowadays, low-cost accelerometers are getting more attention from civil engineers to make Structural Health Monitoring (SHM) applications affordable and applicable to a broader range of structures. The present accelerometers based on Arduino or Raspberry Pi technologies in the literature share some of the following drawbacks: (1) high Noise Density (ND), (2) low sampling frequency, (3) not having the Internet's timestamp with microsecond resolution, (4) not being used in experimental eigenfrequency analysis of a flexible and a less-flexible bridge, and (5) synchronization issues. To solve these problems, a new low-cost triaxial accelerometer based on Arduino technology is presented in this work (Low-cost Adaptable Reliable Accelerometer-LARA). Laboratory test results show that LARA has a ND of 51 µg/√Hz, and a frequency sampling speed of 333 Hz. In addition, LARA has been applied to the eigenfrequency analysis of a short-span footbridge and its results are compared with those of a high-precision commercial sensor.

Assessment of Cracking in Masonry Structures Based on the Breakage of Ordinary Silica-Core Silica-Clad Optical Fibers

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.

Toward a Structural Health Monitoring Methodology for Concrete Structures under Dynamic Loads Using Embedded FBG Sensors and Strain Mapping Techniques

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.

Temperature Sensors Based on Polymer Fiber Optic Interferometer

Temperature measurements are of great importance in many fields of human activities, including industry, technology, and science. For example, obtaining a certain temperature value or a sudden change in it can be the primary control marker of a chemical process. Fiber optic sensors have remarkable properties giving a broad range of applications. They enable continuous real-time temperature control in difficult-to-reach areas, in hazardous working environments (air pollution, chemical or ionizing contamination), and in the presence of electromagnetic disturbances. The use of fiber optic temperature sensors in polymer technology can significantly reduce the cost of their production. Moreover, the installation process and usage would be simplified. As a result, these types of sensors would become increasingly popular in industrial solutions. This review provides a critical overview of the latest development of fiber optic temperature sensors based on Fabry–Pérot interferometer made with polymer technology.

Smart Polymer Composite Deck Monitoring Using Distributed High Definition and Bragg Grating Fiber Optic Sensing

Fiber-reinforced polymer composites are an excellent choice for bridge decks due to high strength, lightweight, resistance to corrosion, and long-term durability with a 100-year design life. Structural health monitoring is useful for the long-term assessment of the condition of the bridge structure and obtaining a response to complex loads considering environmental conditions. Bridge structures have been studied primarily using distributed fiber optic sensing, such as Brillouin scattering; however, critical events, including damage detection, can be missed due to low spatial resolution. There is also a critical need to conduct a comprehensive study of static and dynamic loading simultaneously for fiber-reinforced composite bridge structures. In this study, a novel approach was implemented using two sensor technologies, optical frequency domain reflectometry and fiber Bragg grating-based sensors, embedded in a glass-fiber-reinforced composite bridge deck to simultaneously monitor the deformation response of the bridge structure. The optical frequency domain reflectometry sensor utilizing Rayleigh scattering provides high spatial strain resolution were positioned strategically based on expected stress distributions to measure strain in the longitudinal, transverse, and diagonal directions along the span of the composite bridge. Furthermore, fiber Bragg grating based sensors are used to monitor the response to dynamic vehicular loading and deformations from an automotive-crash-type event on the bridge structure. To monitor environmental variables such as temperature, a custom wireless configured sensor package was developed for the study and integrated with a composite bridge located in Morgan County, Tennessee. Additionally, a triaxial accelerometer was used to monitor the vehicular dynamic loading of the composite bridge deck in parallel with fiber Bragg grating sensors. When appropriate, mid-point displacements were compared with strain-distribution measurements from the fiber optic sensor-based data.

Physics and applications of Raman distributed optical fiber sensing

Raman distributed optical fiber sensing has been demonstrated to be a mature and versatile scheme that presents great flexibility and effectivity for the distributed temperature measurement of a wide range of engineering applications over other established techniques. The past decades have witnessed its rapid development and extensive applicability ranging from scientific researches to industrial manufacturing. However, there are four theoretical or technical bottlenecks in traditional Raman distributed optical fiber sensing: (i) The difference in the Raman optical attenuation, a low signal-to-noise ratio (SNR) of the system and the fixed error of the Raman demodulation equation restrict the temperature measurement accuracy of the system. {ii) The sensing distance and spatial resolution cannot be reconciled. (iii) There is a contradiction between the SNR and measurement time of the system. (iv) Raman distributed optical fiber sensing cannot perform dual-parameter detection. Based on the above theoretical and technical bottlenecks, advances in performance enhancements and typical applications of Raman distributed optical fiber sensing are reviewed in this paper. Integration of this optical system technology with knowledge based, that is, demodulation technology etc. can further the performance and accuracy of these systems.

Concise Historic Overview of Strain Sensors Used in the Monitoring of Civil Structures: The First One Hundred Years

Strain is one of the most frequently monitored parameters in civil structural health monitoring (SHM) applications, and strain-based approaches were among the first to be explored and applied in SHM. There are multiple reasons why strain plays such an important role in SHM: strain is directly related to stress and deflection, which reflect structural performance, safety, and serviceability. Strain field anomalies are frequently indicators of unusual structural behaviors (e.g., damage or deterioration). Hence, the earliest concepts of strain sensing were explored in the mid-XIX century, the first effective strain sensor appeared in 1919, and the first onsite applications followed in the 1920′s. Today, one hundred years after the first developments, two generations of strain sensors, based on electrical and fiber-optic principles, firmly reached market maturity and established themselves as reliable tools applied in strain-based SHM. Along with sensor developments, the application methods evolved: the first generation of discrete sensors featured a short gauge length and provided a basis for local material monitoring; the second generation greatly extended the applicability and effectiveness of strain-based SHM by providing long gauge and one-dimensional (1D) distributed sensing, thus enabling global structural and integrity monitoring. Current research focuses on a third generation of strain sensors for two-dimensional (2D) distributed and quasi-distributed sensing, based on new advanced technologies. On the occasion of strain sensing centenary, and as an homage to all researchers, practitioners, and educators who contributed to strain-based SHM, this paper presents an overview of the first one hundred years of strain sensing technological progress, with the objective to identify relevant transformative milestones and indicate possible future research directions.

Field-Deployable Fiber Optic Sensor System for Structural Health Monitoring of Steel Girder Highway Bridges

Structural health monitoring of highway bridges is a vital but currently challenging aspect of infrastructure engineering due to the number of sensors required, power requirements, and harsh environmental conditions. The purpose of this study is to develop a structural health monitoring system using fiber optic sensors based on fiber Bragg gratings that addresses these issues and is field deployable. Prototype systems were installed on two steel girder bridges. The first bridge used sensors adhered to the web and flange. The second bridge used a flange-only array of mechanically mounted sensors. The results demonstrated the accuracy of the fiber Bragg grating sensors and indicated that fewer multiplexed fiber optic cables and loosely routed cables were needed to maintain signal integrity. Adhered sensors were prone to lose their bond due to the curing conditions in the field. The findings suggest that the proposed system may be best used in a hybrid deployment, where a diagnostic field test with conventional sensors is used to determine the baseline bridge response and fiber optic sensors are periodically installed for short-term monitoring.

Deep learning-based method for the continuous detection of heart rate in signals from a multi-fiber Bragg grating sensor compatible with magnetic resonance imaging

A method for the continuous detection of heart rate (HR) in signals acquired from patients using a sensor mat comprising a nine-element array of fiber Bragg gratings during routine magnetic resonance imaging (MRI) procedures is proposed. The method is based on a deep learning neural network model, which learned from signals acquired from 153 MRI patients. In addition, signals from 343 MRI patients were used for result verification. The proposed method provides automatic continuous extraction of HR with the root mean square error of 2.67 bpm, and the limits of agreement were -4.98-5.45 bpm relative to the reference HR.

Using a non-invasive multi-sensor device to evaluate left atrial pressure: an estimated filling pressure derived from ballistocardiography

BACKGROUND

Heart failure is a global health problem, and elevated left atrial pressure (LAP) is a precursor to identifying decompensated heart failure. At present, out-of-hospital monitoring of patients with heart failure is mostly based on the patient's symptoms and signs, and the use of non-invasive technology is scarce. In this study, a non-invasive ballistocardiography (BCG) device was used to collect thoracic vibration signals generated by heartbeat. We collected these signals from more than 1,000 adults, including those with different heart diseases, and used a sensor system and a composite index related to LAP recognition named the LAP-index, to analyze them. This study aimed to verify the reliability and accuracy of the LAP-index in identifying elevated LAP within heart failure patients.

METHODS

We prospectively included 158 patients with various extent of diastolic function, some of whom had various underlying diseases, and collected BCG and echocardiographic data using a cross-section methodology. The BCG signal was recorded from multiple optical fiber vibration sensors placed on the back of each patient. We adopted the 2016 ASE/EACVI echocardiography guideline as the standard for determining LAP level from echocardiography parameters. To evaluate the diagnostic efficacy of the LAP-index, we drew a receiver operating characteristic (ROC) curve and calculated the area under the ROC curve (AUC).

RESULTS

The LAP-index of the 158 patients ranged from 6 to 32. Of them, 39 were diagnosed as high LAP by echocardiography, and 119 cases had normal or slightly elevated LAP. Comparison of the LAP-index results and echocardiographic results revealed the ROC c-statistic of the LAP-index for identifying high LAP was 0.86 (95% CI: 0.79-0.93; P<0.0001). When the LAP-index was at the best cut-off value of 15.5, the positive agreement rate between it and echocardiography LAP was 0.85, the negative agreement rate was 0.80, and the overall agreement rate was 0.81.

CONCLUSIONS

The sensor system and the LAP-index, a composite index derived from BCG, have high reliability and accuracy in identifying elevated LAP, which provides a novel possibility for the non-invasive detection of hemodynamic congestion in heart failure patients.

Sensing Using Light: A Key Area of Sensors

This invited featured paper offers a Doctrinal Conception of sensing using Light (SuL) as an "umbrella" in which any sensing approach using Light Sciences and Technologies can be easily included. The key requirements of a sensing system will be quickly introduced by using a bottom-up methodology. Thanks to this, it will be possible to get a general conception of a sensor using Light techniques and know some related issues, such as its main constituted parts and types. The case in which smartness is conferred to the device is also considered. A quick "flight" over 10 significant cases using different principles, techniques, and technologies to detect diverse measurands in various sector applications is offered to illustrate this general concept. After reading this paper, any sensing approach using Light Sciences and Technologies may be easily included under the umbrella: sensing using Light or photonic sensors (PS).

Analysis of Reliability of Strain Measurements Made with the Fiber Bragg Grating Sensor Rosettes Embedded in a Polymer Composite Material

The results of strain measuring experiments, with the help of rosettes consisting of fiber Bragg grating sensors (FBG) embedded at the manufacturing stage in a polymer composite material are considered in this paper. The samples were made by the direct pressing method from fiberglass prepregs. A cross-shaped sample was tested under loading conditions corresponding to a complex stress state. A variant of strain calculations based on experimental data is discussed. The calculations were performed under the assumption of a uniaxial stress state in an optical fiber embedded in the material. The obtained results provide a reasonable explanation of the absence in the conducted experiment of two peaks in the reflected optical spectrum, the presence of which follows from the known theoretical principles. The experimental result with two peaks in the reflected optical spectrum was obtained for the same sample under a different loading scheme. The proposed variant of the numerical model of the experiment and the results of numerical simulation made for FBG rosettes embedded in the material allowed to estimate error in the strain values calculated on the assumption of the uniaxial stress state in the optical fiber and in the presence of two peaks in the reflected optical spectrum.

Experimental Strain Measurement Approach Using Fiber Bragg Grating Sensors for Monitoring of Railway Switches and Crossings

Railway infrastructure plays a major role in providing the most cost-effective way to transport freight and passengers. The increase in train speed, traffic growth, heavier axles, and harsh environments make railway assets susceptible to degradation and failure. Railway switches and crossings (S&C) are a key element in any railway network, providing flexible traffic for trains to switch between tracks (through or turnout direction). S&C systems have complex structures, with many components, such as crossing parts, frogs, switchblades, and point machines. Many technologies (e.g., electrical, mechanical, and electronic devices) are used to operate and control S&C. These S&C systems are subject to failures and malfunctions that can cause delays, traffic disruptions, and even deadly accidents. Suitable field-based monitoring techniques to deal with fault detection in railway S&C systems are sought after. Wear is the major cause of S&C system failures. A novel measuring method to monitor excessive wear on the frog, as part of S&C, based on fiber Bragg grating (FBG) optical fiber sensors, is discussed in this paper. The developed solution is based on FBG sensors measuring the strain profile of the frog of S&C to determine wear size. A numerical model of a 3D prototype was developed through the finite element method, to define loading testing conditions, as well as for comparison with experimental tests. The sensors were examined under periodic and controlled loading tests. Results of this pilot study, based on simulation and laboratory tests, have shown a correlation for the static load. It was shown that the results of the experimental and the numerical studies were in good agreement.

Innovative Materials in Italy for Eco-Friendly and Sustainable Buildings

In the last 20 years, there have been a series of seismic events in Italy that have caused serious damage to civil and building structures. This has led to a significant increase in the use of concrete for the reconstruction of new structures and the repair of existing structures damaged by earthquakes. At the same time, the concrete industry is responsible for the most significant environmental damage during the life cycle of the built environment. The environmental disadvantages characterizing the concrete industry are related to the constant growth of the exploitation of natural aggregates. Therefore, it is necessary to use alternative and innovative aggregates that provide good concrete performance and lower environmental impacts. In this study, a very promising route from an environmental point of view is given by the use of artificial aggregates from industrial waste as substitutes for natural aggregates. An innovative low cost and energy saving granulation process has been employed to produce lightweight aggregates using fly ash from the incineration of municipal solid waste and ground granulated blast furnace slag. The final aim of this research is to demonstrate the environmental sustainability of artificial aggregates, through a comparison of three different mixtures.

Recent Advancements in Non-Destructive Testing Techniques for Structural Health Monitoring

Structural health monitoring (SHM) is an important aspect of the assessment of various structures and infrastructure, which involves inspection, monitoring, and maintenance to support economics, quality of life and sustainability in civil engineering. Currently, research has been conducted in order to develop non-destructive techniques for SHM to extend the lifespan of monitored structures. This paper will review and summarize the recent advancements in non-destructive testing techniques, namely, sweep frequency approach, ground penetrating radar, infrared technique, fiber optics sensors, camera-based methods, laser scanner techniques, acoustic emission and ultrasonic techniques. Although some of the techniques are widely and successfully utilized in civil engineering, there are still challenges that researchers are addressing. One of the common challenges within the techniques is interpretation, analysis and automation of obtained data, which requires highly skilled and specialized experts. Therefore, researchers are investigating and applying artificial intelligence, namely machine learning algorithms to address the challenges. In addition, researchers have combined multiple techniques in order to improve accuracy and acquire additional parameters to enhance the measurement processes. This study mainly focuses on the scope and recent advancements of the Non-destructive Testing (NDT) application for SHM of concrete, masonry, timber and steel structures.

Distributed Fibre Optic Sensor-Based Continuous Strain Measurement along Semicircular Paths Using Strain Transformation Approach

Distributed fibre optic sensors (DFOS) are popular for structural health monitoring applications in large engineering infrastructure because of their ability to provide spatial strain measurements continuously along their lengths. Curved paths, particularly semicircular paths, are quite common for optical fibre placement in large structures in addition to straight paths. Optical fibre sensors embedded in a curved path configuration typically measure a component of strain, which often cannot be validated using traditional approaches. Thus, for most applications, strain measured along curved paths is ignored as there is no proper validation tool to ensure the accuracy of the measured strains. To overcome this, an analytical strain transformation equation has been developed and is presented here. This equation transforms the horizontal and vertical strain components obtained along a curved semicircular path into a strain component, which acts tangentially as it travels along the curved fibre path. This approach is validated numerically and experimentally for a DFOS installed on a steel specimen with straight and curved paths. Under tensile and flexural loading scenarios, the horizontal and vertical strain components were obtained numerically using finite element analysis and experimentally using strain rosettes and then, substituted into the proposed strain transformation equation for deriving the transformed strain values. Subsequently, the derived strain values obtained from the proposed transformation equation were validated by comparing them with the experimentally measured DFOS strains in the curved region. Additionally, this study has also shown that a localised damage to the DFOS coating will not impact the functionality of the sensor at the remaining locations along its length. In summary, this paper presents a valid strain transformation equation, which can be used for transforming the numerical simulation results into the DFOS measurements along a semicircular path. This would allow for a larger scope of spatial strains measurements, which would otherwise be ignored in practice.