Search Results (358)

Machine learning (ML)-based techniques have received significant attention in various fields of industry and science. In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. A novel framework based on a combined model and data-driven approach is described, consisting of the establishment of the finite element (FE) model, its updating according to load testing results, and data augmentation to facilitate the training of selected physics-informed regression models. The article discusses the design of the Fiber Bragg Grating (FBG) sensor-based Bridge Weigh-in-Motion (BWIM) system, specifically focusing on several supervised regression models of different architectures. The current work proposes the use of the updated FE model to generate training data and evaluate the accuracy of regression models with the possible exclusion of selected input features enabled by the structural specificity of a bridge. The data were sourced from the SHM system installed on a network arch bridge in Wolin, Poland. It confirmed the possibility of establishing the BWIM system based on strain measurements, characterized by a reduced number of sensors and a satisfactory level of accuracy in the estimation of loads, achieved by exploiting the network arch bridge structural specificity. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

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. Full article

A real-time structural health monitoring (SHM) system of an airplane composite wing with adjustable damage is reported, where testing under realistic flight conditions is carried out in the controllable and repeatable environment of an industrial wind tunnel. An FBG-based sensing array monitors a debonded region, whose compromised structural strength is regained by a set of lockable fasteners. Damage tunability is achieved by loosening some of or all these fasteners. Real-time analysis of the data collected involves Principal Component Analysis, followed by Hotelling’s T-squared and Q measures. With previously set criteria, real-time data collection and processing software can declare the structural health status as normal or abnormal. During testing, the system using the Q measure successfully identified the initiation of the damage and its extent, while the T-squared one returned limited outcomes. Full article

This work presents a hybrid optical fiber detector by combining the sensing mechanism of the fiber Bragg grating (FBG) and the light extinction method to enable the simultaneous measurement of dust concentration and temperature. Compared with the existing dust concentration sensors, the proposed detector offers three key advantages: intrinsic safety, dual-parameter measurement capability, and potentially network-based monitoring. The critical sensing components of the proposed detector consist of two optical collimators and an FBG. Using the extinction effect of light between the two collimators, the dust concentration and temperature are simultaneously determined by monitoring the intensity and the wavelength of the FBG reflectance spectrum, respectively. The measurement feasibility has been evaluated demonstrating that the two parameters of interest can be effectively sensed with minimally coupled outputs of ±3 pm and ±0.1 mW, respectively. Calibration experiments demonstrate that the change in the intensity of light from the FBG is exponentially related to the dust concentration variation with fitting coefficients equal to 0.948, 0.946, and 0.945 for 200 meshes, 300 meshes, and 400 meshes, respectively. The detector’s relative measurement errors were validated against the weighing method, confirming low measurement deviations. Full article

A fiber Bragg grating (FBG)-based ocean temperature and depth sensor structure is proposed. The pressure sensing section employs a secondary sensitization design comprising a piston and the polycarbonate buffer, while the temperature sensing section utilizes an FBG encapsulated within a metal silver tube, accompanied by a temperature compensation structure. Simulation analyses verify the enhanced sensitivity of the proposed configuration. By selecting suitable materials for the piston, metal tube, and polymer, and optimizing the dimensions of key components, the sensitivity of the bare FBG sensor is significantly improved through the combined effects of the piston, polymer, and metal tube. After optimization, the sensor exhibits a pressure sensitivity of 1.33 nm/MPa and a temperature sensitivity of 102.77 pm/°C, meeting the high-precision detection requirements for ocean temperature and depth sensing. The experimental results show that the temperature sensitivity is 109.9 pm/°C within the temperature range of −5~35 °C, and that the pressure sensitivity is 1.63 nm/MPa within the pressure range of 1~10 MPa. These results confirm that the sensor is well-suited for high-precision ocean temperature and depth measurements. Full article

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. Full article

We have developed an adjustable optical fiber Bragg grating (FBG) sensing unit for monitoring nasal breathing. The FBG sensing unit can accommodate individuals with varying facial dimensions by adjusting the connecting holes of the ear hangers. We employed two FBG configurations: an encapsulated FBG within a silicon tube (FBG₁) and a bare FBG (FBG₂). Calibration experiments show the temperature sensitivities of 6.77 pm/°C and 6.18 pm/°C, respectively, as well as the pressure sensitivities of 2.05 pm/N and 1.18 pm/N, respectively. We conducted breathe monitoring tests on male and female volunteers under the resting and the motion states. For the male volunteer, the breathing frequency is 13.48 breaths per minute during the rest state and increases to 23.91 breaths per minute during the motion state. For the female volunteer, the breathing frequency is 14.12 breaths per minute during rest and rises to 24.59 breaths per minute during motion. Experimental results show that the FBG sensing unit can effectively distinguish breathing rate for the same person in different states. In addition, we employed a random forest algorithm to assess the importance of two sensors in breathing monitoring applications. The findings indicate that FBG₁ outperforms FBG₂ in monitoring performance, highlighting that pressure plays a positive impact in enhancing the accuracy of breathing monitoring. Full article

This study introduces a novel deep neural network (DNN) framework tailored to breaking the sampling limit for high-frequency vibration recognition using fiber Bragg grating (FBG) sensors in conjunction with low-power, low-sampling-rate FBG interrogators. These interrogators, while energy-efficient, are inherently limited by constrained acquisition rates, leading to severe undersampling and the obfuscation of fine spectral details essential for accurate vibration analysis. The proposed method circumvents this limitation by operating solely on raw time-domain signals, learning to recognize high-frequency and extremely close vibrational components accurately. Extensive validation using the combination of simulated and experimental datasets demonstrates the model’s superiority in frequency discrimination across a broad vibrational spectrum. This approach is expected to be a significant advancement in intelligent optical vibration sensing and compact, low-power condition monitoring solutions in complex environments. Full article

Free space optics (FSO) aims to perform as one of the best optical wireless channels to design a reliable, flexible, and cost-effective communication system. In FSO systems, mode-division multiplexing (MDM) transmission is a proven technique to expand transmission capacity per communication link. Thus, a 16 × 10 Gbps MDM-FSO system using fiber Bragg grating (FBG) sensors for the coexistence of communication and sensing, exploiting FSO links to transmit distinct Laguerre-Gaussian (LG) beams at a 1000–1900 m range, is proposed. The results illustrate that the system can transmit higher-order LG beams with sensor temperatures of 20–120 °C over a 1500 m range under clear air, drizzle, and moderate haze weather. Also, an improved performance is achieved in gamma–gamma compared to the log-normal distribution model for 10⁻⁶–10^−2.5 index modulation under weak-to-strong turbulence. The proposed system is capable of offering a high optical signal-to-noise ratio (OSNR) and gain of 113.39 and 15.43 dB, respectively, at an aggregate data rate of 160 Gbps under different atmospheric scenarios. Moreover, the proposed system achieves better system performance compared to existing works. Full article

In fiber Bragg grating (FBG) sensing demodulation systems, high-precision peak detection is a core requirement for demodulation algorithms. However, practical spectral signals are often susceptible to environmental noise interference, which leads to significant degradation in the accuracy of traditional demodulation methods. This study proposes a self-adaptive K-SVD (SAK-SVD) denoising algorithm based on adaptive window parameter optimization, establishing a closed-loop iterative feedback mechanism through dual iterations between dictionary learning and parameter adjustment. This approach achieves a synergistic enhancement of noise suppression and signal fidelity. First, a dictionary learning framework based on K-SVD is constructed for initial denoising, and the peak feature region is extracted by differentiating the denoised signals. By constructing statistics on the number of sign changes, an adaptive adjustment model for the window size is established. This model dynamically tunes the window parameters in dictionary learning for iterative denoising, establishing a closed-loop architecture that integrates denoising evaluation with parameter optimization. The performance of SAK-SVD is evaluated through three experimental scenarios, demonstrating that SAK-SVD overcomes the rigid parameter limitations of traditional K-SVD in FBG spectral processing, enhances denoising performance, and thereby improves wavelength demodulation accuracy. For denoising undistorted waveforms, the optimal mean absolute error (MAE) decreases to 0.300 pm, representing a 25% reduction compared to the next-best method. For distorted waveforms, the optimal MAE drops to 3.9 pm, achieving a 63.38% reduction compared to the next-best method. This study provides both theoretical and technical support for high-precision fiber-optic sensing under complex working conditions. Crucially, the SAK-SVD framework establishes a universal, adaptive denoising paradigm for fiber Bragg grating (FBG) sensing. This paradigm has direct applicability to Raman spectroscopy, industrial ultrasound-based non-destructive testing, and biomedical signal enhancement (e.g., ECG artefact removal), thereby advancing high-precision measurement capabilities across photonics and engineering domains. Full article

This paper presents the development and validation of a high-resolution photonic and wireless monitoring system for knee-referenced gait cycle analysis. The proposed system integrates a single optical Fiber Bragg Grating (FBG) sensor with a resonance wavelength of 1547.76 nm and electronic modules with inertial and magnetic sensors, achieving a 10 p.m. wavelength resolution and 1° angular accuracy. The innovative combination of these components enables a direct correlation between wavelength variations and angular measurements without requiring goniometers or motion capture systems. The system’s practicality and versatility were demonstrated through tests with seven healthy individuals of varying physical attributes, showcasing consistent performance across different scenarios. The FBG sensor, embedded in a polymeric foil and attached to an elastic knee band, maintained full sensing capabilities while allowing easy placement on the knee. The wireless modules, positioned above and below the knee, accurately measured the angle formed by the femur and tibia during the gait cycle. The experimental prototype validated the system’s effectiveness in providing precise and reliable knee kinematics data for clinical and sports-related applications. Full article

We present and demonstrate a highly birefringent fiber Bragg grating (Hi-Bi FBG) that was fabricated using a femtosecond laser to induce a sawtooth stress region near the FBG. The FBG is fabricated with a femtosecond laser point-by-point method, while the sawtooth stress region is generated in fiber cladding using the femtosecond laser along a sawtooth path. This sawtooth stressor can introduce an anisotropic and asymmetric refractive index profile in the cross-section of the fiber, resulting in additional birefringence up to 2.97 × 10⁻⁴ along the axial direction of the FBG. The central wavelengths of the Hi-Bi FBG at the fast and slow axes exhibit different sensitivities to temperature and strain, allowing simultaneous measurement of the strain and temperature by tracking the resonant wavelength shifts in the two axes. The experimental results show that the temperature sensitivities of the fast and slow axes are 10.32 pm/°C and 10.42 pm/°C, while the strain sensitivities are 0.91 pm/µε and 0.99 pm/µε. The accuracy of this proposed sensor in measuring strain and temperature is estimated to be 2.2 µε and 0.2 °C. This approach addresses the issue of cross-sensitivity between temperature and strain and offers some advantages of low cost, compact size, and significant potential for advancements in practical multi-parameter sensing applications. Full article

In the context of significant climate change, monitoring inclination, water levels, and temperatures in public buildings and surrounding environments is sensible. This paper presents a pair of fiber Bragg grating (FBG) subsidence sensor systems designed to simultaneously measure tilt and water levels and explore the system’s potential to detect temperature variations. The configuration of the FBG subsidence sensor is intentionally skewed to enhance measurement sensitivity. The system is capable of concurrently detecting a 0.5 cm variation in water level and a 0.424° change in tilt, with tilt measurements spanning from −1.696° to 1.696°. Furthermore, the measurement system can be integrated with free-space optics (FSO), which is anticipated to address the challenges associated with installing fiber optic cables. Consequently, the proposed innovative FBG sensor system can measure multiple parameters using fewer sensors, thereby improving sensing capacity and cost-efficiency. Full article

The increasing demand for high-precision, real-time sensing in various fields has spurred the development of optical fiber grating sensors (OFGSs). This study reviews the research field of OFGSs, exploring their historical development, current trends, and future opportunities through scientometric analysis utilizing CiteSpace. The research landscape has grown exponentially since the early studies on fiber Bragg gratings and long-period fiber gratings in the 1990s. Bibliometric data reveal that engineering, optics, and instrumentation dominate OFGS research, with emerging interdisciplinary applications in environmental, biological, and medical sensing. Key contributors have advanced OFGSs through femtosecond laser inscription, novel materials, and intelligent system integration, as reflected in co-citation and keywords analyses. Trends such as AI-driven optimization, surface plasmon resonance, and 3D printing signal shift toward adaptive, multifunctional sensing systems capable of addressing diverse challenges. This review also maps the evolution of OFGS research, transitioning from foundational strain and temperature sensing to sophisticated systems for structural health monitoring, biomedical diagnostics, and robotics. Despite global disruptions, the field’s recovery highlights its critical role in advancing sensing technologies. By combining thematic insights from co-citation and keyword analyses, this study identifies both established directions and transformative opportunities, providing a holistic understanding of OFGS research and its trajectory. Full article