Distributed Fiber Optic Sensors Research Articles

Pile Capacity Checking Tool based on Distributed Fibre Optic Sensing for Instrumented Pile Load Test

Pile load test instrumented using Distributed Optical Fibre Sensing (DOFS) offers a superior ability to assess pile capacity through continuous strain profiles as opposed to the discrete measurement method such as Vibrating Wire Strain gauges. Due to the vast amount of spatial data generated by the sensor, processing the raw data from DOFS is not always straightforward, often done manually with careful interpretation of various factors affecting the measurements. Experts are reconciling with different data processing algorithms to assess pile capacity (t-z curve) from the DOFS data and verify it, leading to a demand for standard practice. Currently, the verification is done by comparing the pile capacity assessed from DOFS data to the analysis from the commercially available numerical software. The software typically requires input parameters such as extensive soil data, structure geometry, and loading intensity. Some of these parameters are limited (due to bureaucracy or trade secrecy) for the pile load test contractor to verify the pile capacity computation. This paper presents a checking tool that has been developed to automate the processes including raw file parsing, initial processes (trimming, positioning, and averaging), and post processes (pile capacity computation and checking). The post processes utilised the simplified Finite Element Method (FEM) to perform the checking which only utilised the DOFS data. In this paper, an application of the developed tool to a DOFS instrumented pile load test in Kuala Lumpur is reported. This exercise provides the information that the tool can be helpful to verify the pile capacity computation from DOFS data with promising performance reliability at 95%.

A Strain Transfer Model for Detection of Pitting Corrosion and Loading Force of Steel Rebar with Distributed Fiber Optic Sensor.

Steel rebar corrosion is one of the predominant factors influencing the durability of marine and offshore reinforced concrete structures, resulting in economic loss and the potential threat to human safety. Distributed fiber optic sensors (DFOSs) have gradually become an effective method for structural health monitoring over the past two decades. In this work, a strain transfer model is developed between a steel rebar and a DFOS, considering pitting-corrosion-induced strain variation in the steel rebar. The Gaussian function is first adopted to describe the strain distribution near the corrosion pit of the steel rebar and then is substituted into the governing equation of the strain transfer model, and the strain distribution in the DFOS is analytically obtained. Tensile tests are also conducted on steel rebars with artificially simulated corrosion pits, which are used to validate the developed model. The results show that the Gaussian function can be used to describe the strain variation near a corrosion pit with a depth less than 50% of the steel rebar diameter, and the strain distribution in the DFOS analytically determined based on the developed strain transfer model agrees well with the tensile test results. The corrosion pit depth and loading force in the steel rebars estimated based on the proposed model agree well with the actual values, and therefore, the developed strain transfer model is effective in detecting pitting corrosion and loading force in steel rebars.

Water hammer detection based on FIV online analysis using a distributed fiber optic sensor.

In long-distance oil pipelines, the abnormal flow state of the fluid in the pipeline can cause continuous water hammer effects, which can damage the pipeline and even cause leakage or collapse. Based on this phenomenon, this paper proposes a new, to the best of our knowledge, detection method based on sensing optical fiber and phase-sensitive optical time-domain reflectometry (φ-OTDR) system to solve the problem of continuous water hammer detection in long-distance pipelines. The method uses a non-invasive, low-cost, real-time approach to monitor pipeline wall deformation characteristics and assess flow-induced vibration (FIV) intensity by statistically distinguishing water hammer signals from normal vibration signals and calculating the peak-to-average ratio (PAR) of these signals. Experimental results show that the FIV status of different types of pipelines can be effectively monitored by calculating the PAR of water hammer signals and vibration signals. The measured PAR based on the φ-OTDR system has high consistency with the PAR variation trend of simulation results, the distributed fiber optic sensor is less affected by environmental factors, and its detection distance and anti-interference ability are better than those of high-precision commercial triaxial acceleration sensors.

A Comprehensive Study on Measurement Accuracy of Distributed Fiber Optic Sensors Embedded within Capillaries of Solid Structures.

Embedding fiber optic sensors (FOSs) within parts for strain measurement is attracting widespread interest due to its great potential in the field of structural health monitoring (SHM). This work proposes a novel method of embedding FOSs using capillaries within solid structures and investigates fiber positions and orientation uncertainties within capillaries of different sizes and their influences on strain measurement accuracies. To investigate how the fiber positions and orientation variations influence strain measurement accuracy, both analytical and numerical models are utilized to predict strain distributions along embedded fibers at different positions and with different orientations within the specimen. To verify the predictions, a group of specimens made of Aluminum 6082 was prepared, and the specimens in each group had capillaries of 2 mm, 4 mm, and 6 mm diameters, respectively. Fibers were embedded within each specimen using the capillaries. Four-point bending static tests were conducted for each specimen with embedded FOSs, performing in situ strain measurement. Subsequently, the specimens were partitioned into several pieces, and the cross sections were observed to know the real positions of the embedded fiber. Finally, the strain predictions at the real locations of the fiber were compared with the measured strain from the embedded FOSs. The predicted strain distributions as a function of the fiber positions alone and as a function of both the fiber positions and orientations were compared to assess the influence of fiber orientation change. The results from a combination of analytical, numerical, and experimental techniques suggest that the fiber position from the capillary center is the main factor that can influence strain measurement accuracies of embedded FOSs, and potential fiber misalignments within the capillary had a negligible influence. The fiber position-induced measured error increases from 10.5% to 18.5% as the capillary diameter increases from 2 mm to 6 mm. A 2 mm capillary diameter is able to lead to the lowest measurement error in this study and maintains ease of embedding. In addition, it is found that the measured strain always lies within a strain window defined by the strain distribution along capillary boundaries when there are no cracks. This can be further studied for crack detection.

Data-informed statistical finite element analysis of rail buckling

In this paper, the statistical finite element method is developed further to synthesize distributed rail response data with nonlinear finite element model predictions within and outside the measured loading range. In the data-generating model of the statistical finite element method, the distributed sensing data is decomposed into a finite element model component, a model-reality mismatch component, and a noise component. Each component is considered uncertain and is represented as a Gaussian random vector with a corresponding prior density. The finite element prior density is updated using the Bayesian statistical framework in light of the distributed fiber optic sensing data. The calculated posterior density enables one to infer the true structural response. The required finite element prior density is determined by solving a conventional stochastic forward problem using a polynomial chaos expansion of random fields and a non-intrusive pseudo-spectral projection approach. In this paper, a lab test involving a section of a rail (i.e., a beam-column structural member) instrumented with distributed fiber optic sensors and subjected to axial load causing progressive lateral buckling is considered to demonstrate the use of the statistical finite element method to improve rail response prediction. The results show improved prediction of true rail strain in linear and nonlinear regimes compared with a pure finite element model-based prediction.

Effect of stress level and localized corrosion on the strain transfer between corroded steel rebar and distributed fiber optic sensor

Distributed fiber optic sensors (DFOSs) have become an effective tool for deformation and cracking monitoring in reinforced concrete structures due to their multiple sensing points. However, the monitoring accuracy is affected by the strain transfer efficiency between the monitored structural substrate and DFOS. This study experimentally investigates the effect of localized corrosion and stress level on the strain transfer efficiency between corroded steel rebars and DFOS. Steel rebars installed with DFOS were cast in a concrete slab and then subjected to accelerated corrosion tests up to ∼ 12.00% area loss. The residual cross-sectional area distribution of corroded steel rebars was determined based on 3D laser scan data. Tensile tests were conducted, during which the strain distribution of DFOS under different loading levels was recorded with an optical interrogator and then compared with theoretical values. Results show that corrosion does not directly affect the strain transfer efficiency between steel rebars and DFOS, but spatial variation of corrosion causes high strain gradients in steel rebars that result in erroneous strain readings. DFOSs are able to identify the location of big corrosion pits, but the strain transfer coefficient is less than 100% at locations with big corrosion pits while it is over 100% at nearby sections. The strain transfer coefficient increases with an increase in stress level in the elastic stage of steel rebars, while it decreases with an increase in area loss especially for sections with pitting corrosion.

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.

Shear stress analysis in the textile-to-matrix and TRC-to-masonry interfaces of Textile-Reinforced Cement (TRC) applied to masonry using distributed fibre optic sensors

Masonry has been used extensively in civil engineering for centuries. However, various factors can reduce its performance over time. To extend its life and increase its load-bearing capacity, it needs to be reinforced. Strengthening with composite materials, in particular with Textile-Reinforced Cementitious (TRC) matrix composites, has proven to be effective. However, the assessment of the load transfer between TRC and masonry, as well as between matrix and textile at the core of the TRC remains a significant scientific challenge for optimal reinforcement. In this context, this paper aims to contribute to the understanding of the load transfer mechanisms at these interfaces, particularly for shear behaviour.To this end, this study investigates the reinforcement of masonry using TRC. Six different configurations of TRC-to-masonry prisms were subjected to single-lap shear bond tests: two types of textile reinforcements, two types of matrices and two reinforcement ratios. These six configurations were instrumented by distributed fibre optic sensors in the core of the TRC. These sensors measured the mechanical strains of the matrix and textile in the core of TRC with millimetric spatial resolution. From these strains, the local shear stresses and bond behaviour of the textile-to-matrix and TRC-to-masonry interfaces were experimentally quantified, assessed and analysed. A decreasing parabolic trend of these shear stresses along the effective length was obtained before the appearance of cracks, while cracks considerably modify this trend.The contributions of the matrix and the textile to the interface shear stresses were assessed. Before cracking, the contribution of the matrix prevails, while after cracking, the contribution of the textile is predominant. The shear stresses over the TRC thickness were also quantified and analysed. The debonding at the textile-to-matrix interface was tracked and analysed before, during and after crack propagation in TRC. The results obtained confirm that this debonding evolution can be predicted by pull-out tests.

The application of distributed optical fiber sensors (BOTDA) to sinkhole monitoring. Review and the case of a damaging sinkhole in the Ebro Valley evaporite karst (NE Spain)

Distributed optical fiber sensors (DOFS) have been postulated as a suitable technique for long-range monitoring of sinkhole-related subsidence, and possibly for the anticipation of catastrophic collapse (early-warning systems). The strain data published in previous works refer to artificial experiments considering real and virtual cover collapse sinkholes characterized by rapid subsidence and sharp lateral deformation gradients. The influence of the subsidence mechanism (sagging, collapse, suffosion) on the capability of DOFS to satisfactorily detect active subsidence is discussed. Sagging sinkholes with poorly-defined lateral edges, low lateral deformation gradients and slow subsidence are identified as the most challenging scenario. The performance of BOTDA optical fiber for monitoring such type of sagging sinkholes is evaluated in the active Alcalá sinkhole, which affects a flood-control dike creating a high-risk and -uncertainty scenario. This sinkhole shows active subsidence in sections tens of meters long with maximum subsidence rates ranging between 5 and 35 mm/yr. The comparison of vertical displacement data measured by high-precision leveling and the strain recorded by two types of fiber optic cables shows good spatial and temporal correlation. The subsidence sections are captured in the strain profiles by: (1) troughs of negative strain (contraction) in the area affected by subsidence, with the maximum strain associated with the point of most rapid settlement; and (2) lateral ridges of positive values (extension) in the marginal zones. A subsidence acceleration phase associated with a flood is also captured by substantial increments in the strain values. In this challenging scenario, despite the reasonably good spatial and temporal correlation between the displacement and strain data, the unambiguous identification of the active subsidence area with the fiber optic data alone might be difficult. Better results could be obtained improving the monitoring system (e.g., tighter cable-ground coupling) and testing other types of sinkholes with more localized deformation zones and higher subsidence rates.

Back-analysis of sprayed concrete lined (SCL) tunnel junctions at Liverpool Street Crossrail station

Sprayed concrete linings (SCL) offer a versatile method of tunnel construction, particularly in regard to forming junctions since the lining acts as a shell structure which can redistribute the stresses around the opening efficiently. This process is easy to understand conceptually but it is much more difficult to illustrate in calculations. Conventional calculation methods make a number of far-reaching simplifications such as the assumption of linear elastic behaviour in the lining. This often leads to overly conservative designs and a residual concern over the loads in the lining. This study compares detailed measurements of strains recorded by distributed fibre optic sensors at a pair of junctions on the Crossrail project in London with a sophisticated numerical model of these tunnels. Having demonstrated that the results of the numerical model are broadly consistent with this unique set of field data, a variety of influences on the model have been examined. This includes the excavation sequence, the constitutive model for the lining and adjacent structures. The results indicate significant scope for the improvement of SCL junction design. Future papers will present the more results from other parts of this study along with their implications for the design of tunnel junctions.

Assessing Geological Deformation Across Spatial and Temporal Scales Using Distributed Fiber Optic Sensing

Summary This work presents a conceptual framework for assessing geological deformation using distributed fiber-optic sensing (DFOS) that is applicable to several common sources of strain encountered during the reservoir life cycle. Common applications include strain associated with seismic and aseismic fault motion, natural and hydraulic fracture dilation and closure, and poroelastic strain evolution during injection and production. We briefly review common geological sources of strain observed in reservoir settings, then discuss the main fiber-based techniques for recording strain with attention to key deformation characteristics at different spatial and temporal resolutions. The relationships between common acquisition parameters, such as spatial resolution, data sampling rate, ability to measure relative and absolute strain, and a priori knowledge of geological strain including geomechanical models, and the availability of baseline measurements are discussed. Finally, a few examples are shown from experimental studies at the Aramco Research Center in Houston, Texas, USA. The facilities host a shallow vertical well instrumented with fiber as well as a surface fiber network embedded in a cement pad. We highlight several data sets acquired using Brillouin and Rayleigh frequency shift (BFS and RFS), low-frequency distributed acoustic sensing (LF-DAS), and DAS interrogation techniques, with a focus on concepts helpful for interpreting field strain. Using these insights as a conceptual framework for assessing geological deformation leads to more informed decisions when planning DFOS acquisitions and interpreting associated strain data.

Crack Monitoring on Concrete Structures using Robust Distributed Fiber Optic Sensors

AbstractThe possibility to measure strains continuously using distributed fiber optic sensors (DFOS) offers enormous potential for structural health monitoring. Cracks can be automatically detected, localized and crack widths calculated. To address the relevant questions of choosing the right DFOS and appropriate application technique for monitoring existing structures, two 4 m long reinforced concrete beams were loaded under service loads in a 4‐point bending test. The DFOS were either bonded directly to the smooth concrete surface or along a groove. For comparison, another DFOS was integrated into the specimen. It is demonstrated that with the used adhesive, a good strain transfer from the specimen to the DFOS can be ensured even with subsequent installation. In order to detect all cracks with high reliability, robust DFOS with a monolithic cross section should be preferred for the practical use. The accuracy of crack width measurement was verified through Reference measurement via digital image correlation. For the monolithic DFOS, all measurement deviations were within the tolerance range of ±0.05 mm. With layered sensing cables, significant misinterpretations occurred due to strongly damped strain curves.

Investigations on bond performances of GFRP/stainless steel reinforcements using distributed fiber optical sensors (DFOSs)

This study aims to examine the bond behaviors between concrete and glass fiber reinforced polymer (GFRP)/stainless steel bars. Distributed fiber optical sensors (DFOSs) are employed to investigate the tensile and bond behaviors in tension and bond tests. The mechanical properties of two different types of GFRP bars and one type of stainless steel bar are determined through tension tests, while the accuracy of the DFOSs is evaluated through comparison with reference methods such as strain gauge and extensometer. The bond tests aim to investigate the bond behaviors between concrete and the reinforcement bars, with a particular emphasis placed on a type of GFRP bars with a grey coating. Furthermore, the study compares the results obtained from DFOS in the bar groove and DFOS on the bar surface. In addition, the impact of various DFOS coatings and adhesives on the measured bar strains is investigated. The best combination of DFOS and adhesive is identified and applied to other bars to analyze the differences in strain distribution. Finally, the research concludes by presenting and analyzing the full strain distributions along the three different types of embedded bars. Overall, the research provides novel insights into the full bond behaviors between concrete and GFRP/stainless steel reinforcement bars and highlights the effectiveness of DFOSs in measuring strain during bond tests.

Experimental validation of DFOS monitoring system for a bridge girder made of wind turbine blade

AbstractThe relatively new fibre optic measurement technique: distributed fibre optic sensing (DFOS) is provided to control strains and displacements, used in the structural health monitoring of a decommissioned wind turbine blade (WTB) bridge girder. The DFOS system is characterized by the following features: accurate, reliable and continuous strain measurements, possibility of assessing shape and displacements, detection of local damages, high durability. Exemplary results of DFOS measurements performed under laboratory conditions on the full‐scale WTB bridge girder are presented. The paper describes the concept of the WTB bridge girder with integrated DFOS monitoring system to control the girder's behavior under loading. Exemplary data of DFOS efficiency were presented and the overall accuracy and reliability of the DFOS measurement system were revealed.

Experimental verification of FRP bridge deck's monitoring system based on DFOS sensors

AbstractThe paper presents the smart FRP composite bridge panel called „OptiDeck“ with integrated distributed fibre optic sensors (DFOS), to monitor the panel's behavior. The panel is intended for use in newly build and refurbished road bridges. From structure point of view the uniqueness of the presented solution results from innovative technological production process to create a honeycomb core in thick sandwich panel. In order for the monitoring system to cover the entire surface of the panel and to detect local damage, it was necessary to use a modern solution based on geometrically continuous DFOS system. The DFOS system serves as the structure health monitoring (SHM) system, which has been tested during the production and laboratory testing of a prototypes in natural scale. The advantages of DFOS measurements are well known and applied in many civil engineering applications. However, the potential benefits are still not fully utilized. Finally the experimental verification of the DFOS system integrated with the FRP deck panel is presented.

Towards an Automated Crack Monitoring using Distributed Fiber Optic Sensors

AbstractThe high spatial resolution of distributed fiber optic sensors enables quasi‐continuous strain measurements, which makes it a promising technology for structural health monitoring. From this quasi‐continuous strain data, location and width of cracks can be estimated. For major benefit to infrastructure maintenance, this crack width calculation is need to be automated. A framework for crack width estimation is presented, streamlining the different approaches for concrete and steel sensors, mainly differing in the compensation of tension stiffening. Relevant parameters for the analysis are identified and their influence is studied. Two sensors – a concrete embedded one and a reinforcement attached one – are used to estimate crack width using the presented framework. The results are compared to digital image correlation. Accurate estimates are achieved. Tension stiffening showed to have a negligible small influence on the estimated crack widths. The concrete embedded sensors have a higher sensitivity and are recommended for crack width monitoring.

Strain, crack, stress and shape diagnostics of new and existing post-tensioned structures through distributed fibre optic sensors

Prestressed concrete is commonly used in the construction of safety–critical structures such as large-span girders or slabs. The article focuses on post-tensioned elements, in which curvilinear multiwire strands are tensioned after concrete’s hardening to transfer the compressive force to the concrete. The overall idea is to confront external forces and achieve extended benefits, e.g. longer spans or reduced cracking. However, the design, construction and maintenance of such elements are particularly challenging because of their complexity, including spatial stress state in the anchorage zones and also the standard features of concrete structures like heterogeneity, material imperfections and, most importantly, local discontinuities (cracks). Reliable diagnostic solutions are therefore essential for both new and existing components. Distributed fibre optic sensing (DFOS) allows the measurements to be taken continuously over the entire structural length and its advantages have already been proven in civil engineering applications, especially those related to concrete structures. However, the novelty of the presented research lies in 1) simultaneous analysis of strains, stresses, cracks and displacements (shape changes); 2) direct comparison of results from monolithic sensors embedded in the concrete (for new structures) and those installed in pre-made near-to-surface grooves (for existing structures); 3)the application of the embedded composite strain sensor to the bi-directional analysis of the stress field within the anchorage zones; 4) possibility of strain transfer analysis between the cracked concrete, cable duct, injection and prestressing tendon during mechanical bending tests. The DFOS-based strain, crack and displacement results were also compared with reference measurements made with conventional spot techniques, achieving very good compliance. The research proved that a well-designed DFOS-based system, including appropriate measurement techniques, optical sensors, installation methods and post-processing algorithms, is the relevant tool for the diagnostics of post-tensioned concrete structures.

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.

Intelligent monitoring of spatially-distributed cracks using distributed fiber optic sensors assisted by deep learning

Distributed fiber optic sensors (DFOSs) offer unique capabilities for crack monitoring via measuring strain distributions. However, manually interpreting strain distributions is labor-intensive and time-consuming. To address this challenge, this paper presents a deep learning approach for real-time automatic interpretation of strain distributions, aiming at monitoring spatially-distributed cracks. The proposed approach encompasses three key innovations. First, deep learning-based methods are developed to facilitate automatic detection and localization of spatially-distributed cracks. Second, transfer learning is incorporated to overcome the data scarcity issue in training deep learning models. This ensures robust performance even with limited data. Third, a split-and-merge method is developed, enhancing the accuracy of multi-crack detection. To evaluate the performance of the approach, experimental data from various cases were considered. The results demonstrate a mean average precision (mAP) of 0.968 for crack detection. The processing time for a set of DFOS data, containing 10,000 measurement points, was less than 0.05 s.

Strain Transfer Mechanism in Surface-Bonded Distributed Fiber Optic Sensors under Different Strain Fields.

Mastering the strain transfer mechanism in distributed fiber optic (DFO) sensors holds the key to analyzing strain measurement errors from DFO sensing systems. However, the impact of the monitored structure's strain distribution on the strain transfer mechanism in DFO sensors has often been overlooked in the existing research. To address this issue, a strain transfer model of surface-bonded DFO sensors with multilayered structures was established based on the shear lag theory. The closed-form solutions of the strain transfer coefficient of DFO sensors subjected to uniform, parabolic, single-linear gradient, and bilinear gradient strains were obtained. With a high-accuracy optical frequency-domain reflectometer (OFDR), the theoretical model was validated by laboratory tests. Upon parametric analysis, suggestions were further offered about designing and installing DFO sensors.