The internal information of pavement structure is difficult to be accurately obtained by mechanical theory due to the multimedia of component materials and the complex interfacial contacting conditions, and the lab tests are affected by model scale and simplification of loads. Therefore, it is of great significance to accurately obtain the internal information of the structure. The fiber Bragg grating (FBG) sensing technology has thus been adopted to monitor the long-term information of temperature fields and temperature variation induced strain inside the pavement structure. Based on the long-term monitoring data, statistical analysis aided with regression algorithms has been performed to establish the temperature prediction model at each depth of the cement concrete pavement. The results show a high quadratic polynomial correlation between pavement temperature and pavement depth. To confirm the effectiveness of the proposed models and techniques, finite element simulation analysis based on ABAQUS software is performed. The feasibility and accuracy of the developed pavement monitoring system for long-term continuous structural health monitoring is proved. The field data indicates that the heat transfer weakening effect due to the structural materials has a gradual lag in the time between the peaks and valleys of the temperatures at each layer of the structure. By analyzing the temperature variation induced strain field of the pavement structure, certain data references are provided for the preventive maintenance, design and construction of rigid pavement structures. The study provides scientific instructions for assess the performance of the pavement under long-term environmental temperature actions and efficient temperature prediction model for preventive control of the large temperature gradient induced deformation effect in rigid pavements in Gansu Province.

Due to the complexity of interlayer interaction and the composition medium, the structural performance of the pavement structure is difficult to accurately calculate. It is particularly important to analyze the mechanical behavior based on the in situ monitoring data. Industrialized optical fiber sensors (such as fiber Bragg grating (FBG) pressure sensor, temperature sensor, and glass fiber-reinforced polymer (GFRP)-packaged quasidistributed FBG sensor) and their characterization methods for measuring multiple parameters have been developed and embedded in different structural layers of the asphalt pavement in cold regions. According to the periodic in situ monitoring information, the temperature at different positions in the asphalt pavement layer is nonuniformly distributed. The pressure sensors distributed in the cement-stabilized gravel base and the asphalt concrete course can sensitively perceive the vertical deformation of the pavement. Under the temperature action, vertical tensile strains at local points of the asphalt course layer and the base layer indicate that a void phenomenon exists inside the surface layer. Affected by low temperature and temperature changes, there is an obvious expansion and contraction cycle inside the pavement. The validity of the monitoring data shows that the FBG sensors embedded in asphalt pavements can accurately detect the structural characteristics and can be used for long-term continuous monitoring of asphalt pavements in cold regions, which can contribute to the efficient evaluation and maintenance of pavement service performance.

Internal responses of multilayer pavement structures are difficult to characterize using surface-based inspection alone. This study investigates a scaled multilayer pavement model instrumented with embedded quasi-distributed fiber Bragg grating (FBG) sensing lines to obtain baseline internal strain responses and FBG-derived relative vertical displacement distributions under controlled loading. Central single-point stepwise loading, symmetric two-point loading, and asymmetric two-point loading were applied, and FBG wavelength responses were converted into temperature-compensated strain and then into line-wise relative vertical displacement through strain–curvature conversion, curvature integration, and linear baseline correction. During loading, the ambient temperature ranged from 22.70 to 23.40 °C, and the maximum relative shift of the T-sensor was 0.008297 nm. Under 686 N central loading, SAL1 reached a maximum temperature-compensated strain of 1459.39 με and a maximum relative vertical displacement of 1.079 mm, whereas SAL2 reached 793.13 με and 0.583 mm. Under approximately 490 N asymmetric two-point loading, SAT2 reached 1699.48 με and 0.761 mm. Soil-base responses were substantially lower. Because no independent displacement measurement was acquired, the reconstructed quantity is interpreted as an FBG-derived relative deformation measure rather than an absolute displacement. The results establish intact baseline data for future, separately validated comparisons with abnormal conditions.

Real-time monitoring of internal pressure changes of vacuum pressure vessels is particularly important in the aerospace industry, which can be adopted to instruct the fault analysis. Considering the poor measurement accuracy of traditional vacuum gauges, this paper provides the optical fiber-based sensing technology combined with the theoretical characterization of stress and strain distributions of vacuum vessels for reflecting the vacuum degree curves with high precision. The design and deployment of quasi-distributed fiber Bragg grating (FBG) sensors are then carried out to construct a real-time monitoring system. Statistical analysis is further performed to establish the modification coefficient to decrease the vibration effect on the testing signals during the vacuum extraction and unloading process, and wavelet denoising theory has also been adopted to further improve the accuracy of the experimental data, which shows higher accuracy of the monitoring parameter after the correction. The research results show that the integration of FBG sensing technology, statistical signal analysis, and processing algorithms can realize the real-time, sensitive, and high-precision monitoring of the vacuum degree curve, with the measurement accuracy enhanced by 50%, which can be used to replace traditional vacuum gauges. The study realizes real-time and accurate monitoring of the vacuum degree inside the pressure vessel based on the proposed FBG sensing technology and algorithms. It can be instructive for recognizing the fault state of the vacuum pressure and maintaining the stable and safe storage of energy resources.

Carbon fiber-reinforced polymer (CFRP) composites are increasingly used in aerospace, rail transportation, and energy engineering owing to their high specific strength and corrosion resistance. However, their complex and interacting damage mechanisms, including delamination and matrix cracking, present significant challenges for reliable structural health monitoring. Fiber Bragg grating (FBG) sensors offer distinct advantages for monitoring composite structures because of their compact size, immunity to electromagnetic interference, embeddability, and capability for distributed strain measurement. Nevertheless, the effectiveness of an FBG sensing network depends strongly on the spatial distribution of the sensing points. This study proposes a finite-element-assisted framework for evaluating and improving FBG sensor layouts for strain-field reconstruction and structural feature characterization of composite plates. The framework first reconstructs the spatial strain field from limited sensing data using interpolation and least-squares fitting methods, and then evaluates the performance of existing and candidate sensor layouts based on reconstruction errors and spatial coverage of structurally important regions. A strain-gradient-informed heuristic strategy is subsequently developed to improve sensor placement by combining high-gradient region identification, spatially uniform coverage, minimum-distance constraints, and predefined support-region monitoring requirements. The Fourier least-squares fitting method provides the lowest reconstruction error among the investigated approaches and is therefore adopted for subsequent layout evaluation and improvement. Finite-element simulations and experimental measurements are used to assess the reconstruction performance and identify the advantages and limitations of different sensor layouts under static and dynamic loading conditions. The results demonstrate that the proposed framework can effectively evaluate existing FBG layouts and provide a systematic basis for their improvement, while also revealing the trade-off between local strain-gradient resolution and global spatial coverage. The proposed framework provides practical guidance for the performance-oriented design and improvement of FBG sensor networks for structural health monitoring of composite structures.

The interfacial properties of multi-layer composite structures govern their overall load-bearing capacity. Therefore, it is necessary to investigate the influence of interfacial degradation on the internal force transfer mechanism of multi-layer composite structures. This paper proposes an improved interfacial degradation analytical model that can be directly invoked within the transfer matrix method framework. By continuously adjusting the elastic modulus of a thin transfer layer, the model simulates the life cycle of an interface, from ideal bonding to complete slip state. This approach overcomes the limitations of conventional models with difficulty to calibrate interfacial parameters. The reliability of the theoretical model has been verified through finite element calibration of interfacial parameters. Furthermore, specially packaged multifunctional fiber Bragg grating (FBG) sensors for strain and temperature measurement of pavement has been developed, and a multi-scale optical fiber monitoring network covering both local and global areas has been established for in-site monitoring of multi-layer pavement structures. Using the continuous monitoring data in 5 years, a non-destructive method for assessing interfacial degradation based on plastic deformation propagation is proposed. The results reveal that the temperature sensitivity of the structural concrete surface layer initially increases, then decreases before gradually stabilizing, thereby clearly characterizing the entire process of interfacial degradation. In-site vehicle loading tests indicate that the actual interfacial contact conditions between structural layers are semi-continuous and semi-smooth, with these boundary conditions significantly reducing the decay rate of horizontal structural stresses. This study establishes a closed-loop research framework integrating “Theory-Numerical Simulation- Monitoring in Field”, providing innovative concepts and mature techniques for the long-term performance prediction and precise maintenance decision-making of multi-layer composite pavements.

Carbon fiber reinforced polymer (CFRP) laminates are widely used in aerospace, new energy, and transportation engineering due to their high specific strength and stiffness. However, interlaminar delamination damage can lead to sudden structural failure, and the occurrence and prediction of such hidden defects are difficult to identify and evaluate using conventional inspection methods. To address this, smart CFRP laminates integrated with fiber Bragg grating (FBG) sensors offer a new approach for real-time structural health monitoring (SHM). Nevertheless, the influence mechanisms of the two integration methods—embedded and surface-bonded FBG sensors—on the static strength and impact resistance of the structure remain unclear. To fill this gap, this paper systematically investigates the mechanical behavior under static and dynamic loads and the optimization strategies for impact resistance of smart CFRP laminates with embedded/surface-bonded FBG sensors through a combination of experimental and simulation methods. Orthogonally laid-up CFRP laminates were designed and fabricated, integrated with FBG sensor arrays to form a primary self-sensing system. The strain characteristics of the CFRP laminate structures with different FBG integration methods were quantitatively analyzed through static loading and low-velocity impact tests. Furthermore, a multi-scale finite element model was established based on LS-DYNA to validate the experimental trends and reveal the underlying mechanisms. The research results indicate that the strain amplitude decays inversely with the distance from the sensor to the loading point, the strain response exhibits typical “four-stage characteristics,” the peak strain is positively correlated with the impact energy, and it decays exponentially with sensor distance. The finite element simulations show high consistency with the experimental strain trends, verifying the reliability of the established multi-scale model. Within the linear-elastic, non-damaging regime considered in this study, the finite element simulations indicate that embedded optical fibers slightly redistribute the local stress field but have only a limited influence on the global impact response of the CFRP laminate. These findings provide scientific instruction for the development of smart CFRP structures and the configuration of FBG-based SHM system.

Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity. A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential, as it offers intuitive insights into parametric influences and facilitates enhanced structural performance. This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures. By establishing a twodimensional composite pavement model, it investigates load transfer characteristics and validates the accuracy through finite element simulation. The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers. Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses. The soil base layer reduces the overall mechanical response of the substructure, while horizontal actions increase the risk of interfacial slip and cracking. Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer, enhancing the thickness and stiffness of the soil base layer, or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking. The findings of this study can guide the optimization design, parameter analysis, and damage prevention of multi-layer composite structures.

This study investigates the use of cotton ropes (CRs) as a sustainable and cost-effective substitute for synthetic fiber-reinforced polymers for concrete confinement, offering significant environmental benefits such as lower CO2 emissions and reduced energy consumption. The work evaluates the effectiveness of CR strips for confining concrete, including scenarios with recycled concrete aggregates (ReCA). Compressive strength improvements varied among specimens, with Specimen I-3F showing a 140.52% increase and Specimen II-3F achieving a 46.67% improvement. Strip configurations for Type I recycled aggregate concrete (RAC) outperformed full wraps on Type II RAC, exemplified by Specimen I-3S’s 84.51% improvement. Ultimate strain enhancements ranged from 915% to 4490.91%, driven by the significant rupture strain of cotton rope confinement. For Type I RAC, complete wrapping significantly outperformed strip configurations by 56%, 50%, and 32% in ultimate strength improvement for 1, 2, and 3 layers, respectively. The confinement ratio, varying from 0.10 to 0.70, greatly influenced the compressive behavior, with compressive strength normalized by unconfined strength increasing consistently with the confinement ratio. A minimum confinement ratio of roughly 0.40 is required to achieve an increasing second part in the compressive behavior. The initial parabolic branch was modeled using Popovics’ formulation, revealing an elastic modulus approximately 20% lower than ACI 318-19 predictions. The second branch was described using a linear approximation, and nonlinear regression analysis produced expressions for key points on the idealized compressive curve, enhancing model accuracy for CR-confined RAC. The R2 values for the nonlinear regression analysis performed on experimental results were greater than 0.90. This study highlights the effectiveness of neural network expressions to predict the compressive strength of CR-confined concrete. A strength reduction (ratio of full wrap and strip wrap height CRs) factor of 0.67 was proposed and used for strip-wrapped specimens. It was seen that the neural network models also predicted the compressive strength of partially wrapped specimens with reasonable accuracy using the strength reduction factor.

The wide-spread application of carbon fiber-reinforced polymer (CFRP) composites in industrial fields has led to high demand for developing a rapid detection method for assessing the structural performance of CFRP composites in operation based on optical fiber sensing technology. Therefore, the effectiveness and reliability of evaluating the fatigue resistance of CFRP plates based on fiber Bragg grating (FBG) monitoring information were explored. The strain response of CFRP plates at key positions under constant amplitude fatigue load was monitored by bare FBGs in series and packaged quasi-distributed FBGs in series. The structural performance and fatigue resistance characteristics of CFRP plates were evaluated by statistical analysis and fatigue life prediction theory. The validity and accuracy of the test and analysis results were demonstrated by finite element modeling analysis. Compared with the traditional methods that evaluate the structural fatigue performance based on mass destructive experiments, this method significantly improves the detection efficiency and realizes the non-destructive and rapid online evaluation of structural service performance. Research shows that the designed FBG sensors can effectively monitor the strain response of CFRP plate under fatigue load, and the correlated fatigue algorithm can provide feasible and reliable technical approaches for online detection and evaluation on the structural performance of CFRP components.

Vacuum pressure vessels are one of the critical components in the aerospace field, and understanding the mechanical behavior feature is particularly important for safe operation. Therefore, it is meaningful to obtain the stress and strain distributions in the key positions of the vacuum tank, which can contribute to the safe performance assessment, operation efficiency, and fault analysis. Hence, this paper provides the distribution characteristics and variation rules of stress and tank strain of vacuum under different internal and external pressures through the elastic theoretical analysis and iteration method. The quasi-distributed fiber Bragg grating (FBG) sensors and the layout on the vacuum pressure vessel have thus been designed to monitor the whole vacuum extraction and loss process under three different loading conditions. Data analysis based on the theoretical results and monitoring information has further been conducted to validate the effectiveness of the proposed monitoring method for possible leakage defects. Research results indicate that the continuously monitoring data can quite sensitively and accurately characterize the microstrain variation features of the vacuum tank at different vacuum stages, and the loading-induced vibration effect should be carefully considered during the data interpretation. The study can provide scientific support for the vacuum loss state monitoring and safe performance assessment of the vacuum pressure vessels.

As a key storage facility, the structural safety of large oil tanks is directly related to the stable operation of the energy system. The static pressure caused by the change of liquid level is one of the main loads in the service process of storage tanks, which determines the structural deformation and damage risk. To explore the structural deformation properties under the change of liquid levels and provide a theoretical basis for the prevention and control of damage risk, this paper systematically analyzes the mechanical response of storage tanks under the pressures induced by different liquid levels based on the shell theory. Combined with the finite element software COMSOL, the radial displacement and stress-strain distribution under different liquid levels are simulated to verify the accuracy and effectiveness of the proposed theoretical model. The increase in liquid level and radius aggravates the radial deformation and makes the risk point move up, while the increase in wall thickness can effectively reduce the deformation response. Suggestions on the monitoring zone and damage risk prevention measures have also been given to instruct the safe operation of oil tanks. The research provides theoretical support for the optimization design of storage tank structures, the construction of advanced structural health monitoring system and the prevention and control of damage risk.

Timely detection of leaks is essential for the safe and reliable operation of pressure vessels used in superconducting systems, aerospace, and medical equipment. To address the lack of efficient online leak detection methods for such vessels, this paper proposes a quasi-distributed fiber Bragg grating (FBG) sensing network combined with theoretical stress analysis to diagnose vessel conditions. We analyze the stress-strain distributions of vacuum vessels under varying pressures and examine stress concentration effects induced by small holes; these analyses guided the design and placement of quasi-distributed FBG sensors around the vacuum valve for online leakage monitoring. To improve measurement accuracy, we introduce a vibration correction algorithm that mitigates pump-induced vibration interference. Comparative tests under three leakage scenarios demonstrate that when leakage occurs during vacuum extraction, the proposed system can reliably detect the approximate leak location. The results indicate that combining an FBG sensing network with stress concentration analysis enables initial localization and assessment of leak severity, providing valuable support for the safe operation and rapid maintenance of vacuum pressure vessels.

This study investigates the compressive behavior and self-sensing performance of circular hollow section (CHS) stocky steel short tubes strengthened with externally bonded basalt fiber-reinforced polymer (BFRP) sheet with embedded fiber Bragg grating sensors (FBGs). Twenty-four CHS columns, with or without strengthening, were tested under axial compression, while six additional specimens were used to evaluate the sensing functionality of FBGs. The results show that BFRP confinement enhanced the yield load and axial shortening of 4 mm tubes by up to 26 % and 23 %, respectively, while additional BFRP layer reduced lateral strain and increased post-peak energy dissipation by up to 32 %. The FBGs demonstrated good strain sensitivity of accuracy within +/- 1.5 %, effectively capturing confinement activation and strain evolution. Modified design rules generally predicted sectional capacities with further consideration on FRP confinement effects. Finally, BFRP strengthening exhibited higher weight- and cost-efficiency than GFRP, underscoring its potential for multifunctional strengthening and structural health monitoring applications.

Carbon fiber-reinforced polymer (CFRP) laminates have been widely coated on aged and damaged structures for recovering or enhancing their structural performance. The health conditions of the coated composite structures have been given high attention, as they are critically important for assessing operational safety and residual service life. However, the current problem is the lack of an efficient, long-term, and stable monitoring technique to characterize the structural behavior of coated composite structures in the whole life cycle. For this reason, bare and packaged fiber Bragg grating (FBG) sensors have been specially developed and designed in sensing networks to monitor the structural performance of CFRP-coated composite beams under different loads. Some optical fibers have also been inserted in the CFRP laminates to configure the smart CFRP component. Detailed data interpretation has been conducted to declare the strengthening process and effect. Finite element simulation and simplified theoretical analysis have been conducted to validate the experimental testing results and the deformation profiles of steel beams before and after the CFRP coating has been carefully checked. Results indicate that the proposed FBG sensors and sensing layout can accurately reflect the structural performance of the composite beam structure, and the CFRP coating can share partial loads, which finally leads to the downward shift in the centroidal axis, with a value of about 10 mm. The externally bonded sensors generally show good stability and high sensitivity to the applied load and temperature-induced inner stress variation. The study provides a straightforward instruction for the establishment of a structural health monitoring system for CFRP-coated composite structures in the whole life cycle.

Pipeline structures are crucial in the transportation of national strategic and public resources such as oil, gas, and water. Due to the erosion caused by the transported media and the surrounding environment, pipe structures are prone to damage such as micro-cracks, frictional wear or corrosion-induced perforations, which may ultimately lead to the leakage of the internal media. It is thus particularly important to establish a smart health monitoring system to efficiently and promptly identify damages in pipeline structures. Therefore, this paper proposes a semi-automatic structural damage identification method based on monitoring data from fiber Bragg grating (FBG) sensors and modal parameters identified by the improved covariance-driven stochastic subspace identification (SSI-COV) method. Two types of packaged FBG sensors have been adopted to measure data of the pipe under natural excitation. Results demonstrate that the use of empirical formulas for system order and delay time in the SSI-COV method, combined with stability diagrams for eliminating spurious modes, enables the filtered data to discard noise-dominated information, thereby improving both computational efficiency and damage identification accuracy. When the natural excitation is insufficient, the identified modal parameters may contain significant errors. Therefore, an optimization method is further introduced to improve the accuracy of the identified modal parameters. Experimental results demonstrate that the damage index (DI) calculated by using the modified modal parameters can effectively locate damage at the peak value. The structural damage identification analysis confirms that the proposed method can efficiently identify damage in a short time with strong robustness. With short data processing time and high efficiency, this method supports the development of real-time health monitoring systems and enables fast damage detection in pipeline structures.

Pipes may have leakage, breakage, and local blockage during the long-term service period, which may lead to insufficient flow velocity and low water supply pressure. Therefore, measuring flow velocity in pipes is crucial for diagnosing damage, ensuring safe operation, and managing maintenance. Current flow velocity measurement techniques exhibit poor stability over long-term measurements in complex environments, and the measurement quality is affected by the physical and chemical properties of the transported medium. To address these issues, this study employs distributed optical fiber sensors (DOFSs) for measuring flow velocity in water-filled pipes, and the effectiveness is validated by the fiber Bragg grating (FBG) sensors. Based on the phase change of optical fiber demodulated by a distributed acoustic sensing (DAS) device, the flow velocity is accurately measured. Test results demonstrate a quadratic relationship between flow velocity and phase change of optical fiber based on the DAS system, with all fitting effects exceeding 0.95, consistent with theoretical analysis. The influence of different sensor layouts of the distributed optical fibers on the monitoring data is also carefully checked, and the testing results show that bonding the optical fiber on the pipes can achieve better measurement quality, compared to the free optical fiber without constraint around the pipe. This study contributes to improving the measurement accuracy and stability of optical fiber sensors by using the DAS system.

Significance The construction scale of large-scale infrastructure in China has ranked first in the world for many years.Meanwhile,due to construction quality,using environment,natural disasters,and other factors,serious accidents occur frequently.Distributed optical fiber sensing technologies employ optical fibers as signal transmission medium and sensing units to realize continuous distributed measurement of external parameters along the optical fiber.Therefore,it is the most potential non-destructive monitoring technology for large-scale infrastructure health monitoring in real time.However,distributed fiber optic sensing technologies still face various challenges such as reliability,low cost,and intelligence as they move toward the market. Progress At present,distributed optical fiber sensing technologies that have caught extensive attention and research include optical time-domain reflectometer,coherent optical time-domain reflectometer,phase-sensitive optical time-domain reflectometer,optical frequency-domain reflectometer,Raman optical time-domain reflectometer,Brillouin scattering optical time-domain reflectometer,Brillouin optical time-domain analyzer,and optical interferometry.We focus on introducing their working principles,system basic structures,development history,current status,and major research institutions and manufacturers at home and abroad. Based on detailing the application requirements,principles,and methods of distributed optical fiber sensing technologies in communication system monitoring,power system monitoring,coal geology monitoring,oil and gas exploration,transportation field,transportation pipeline monitoring,aerospace equipment monitoring,and perimeter security,we provide several typical application cases. Conclusions and Prospects The future main directions of development are listed: 1)Multi-mechanism integration system.Single sensing parameters make it difficult to represent the true state of the measured object,which can result in false reports and missed reports.Simultaneous measurement of multiple parameters can provide multidimensional and more comprehensive information,thereby more accurately identifying fault events.The key point of the fusion-type distributed optical fiber sensing technology is to employ different scattering lights to respond to different events in the optical fiber to achieve multi-parameter sensing. 2)Specialty sensing fiber cable technology.By changing the fiber material,structure,and packaging,specialty optical fiber cables can overcome the limitations of distributed sensors based on ordinary single-mode optical fibers,and obtain engineering applications in specific sensing parameters and performance in specific fields and scenarios. 3)Sensing signal processing and intelligent perception technology.Due to the weak intensity of scattered light compared to incident light,distributed sensing systems are limited by signal-to-noise ratio.This affects the measurement accuracy,monitoring distance,response speed,spatial resolution,and other key indicators of distributed sensing systems.Signal processing techniques to analyze and enhance collected data are important means to improve the performance of sensing systems. 4)Communication-sensing fusion system.Technologies such as wavelength division multiplexing,polarization diversity,and coherent detection from optical communication systems are applied to distributed fiber optic sensing systems.Additionally,existing optical fiber communication systems can be adopted for synchronous sensing.These are crucial steps towards the practical applications of distributed fiber optic sensing systems. 5)Distributed shape sensing technology.Leveraging distributed fiber optic sensing technology for shape sensing is an important development direction. 6)Ocean state monitoring based on existing optical cables.Existing undersea optical communication networks are employed as sensing networks to achieve intelligent perception of the surrounding environment of the cables.This enables large-scale online monitoring and early warning capabilities with relatively low investment,thus providing rapid and accurate assurance for managing major maritime incidents and maritime disaster risks.

In order to investigate the damage process caused by the seismic pseudo-static load, quasi-distributed fiber bragg grating (FBG) sensors were placed in CRTS III ballastless track specimens. Low-cyclic reversed load experiments were then carried out. We studied the strain conditions at various points along the ballastless track under cyclic loading as well as the damage modes, strain curves, residual strains, and cross-sectional stresses of the self-compacting concrete layer and foundation slab. The damage process may be broken down into three stages: First, fractures show up at the base plate anchors; second, the shear reinforcement deforms; and third, the concrete layer is lifted until it is crushed. The CRTS III ballastless slab's maximum transverse tensile strain is greater than its maximum longitudinal tensile strain. Premature cracking of the self-compacting concrete layer will result from greater strain at the edge and corner of the groove and from a lack of reinforcing. It is tough to monitor the deformation of the groove area at simultaneously, which is not possible with more conventional monitoring methods like strain gauge sensors. Quasi-distributed FBG sensing can effectively observe the detailed strain development of the groove and its surrounding areas.