Search Results (2,776)

In early-warning scenarios for thermal runaway in energy storage batteries, carbon monoxide (CO) may interfere with hydrogen detection and reduce the reliability of signal interpretation. To mitigate CO cross-interference under representative mixed-gas conditions and improve sensing stability, a fiber-optic microelectromechanical systems (MEMS) hydrogen sensor based on a Pd–Cu alloy-sensitive layer was developed. The sensor employs a single-cantilever structure and a reflective Fabry–Pérot (F–P) interferometer for optical readout. Comparative experiments were carried out using sensors coated with pure Pd and Pd–Cu-sensitive layers under pure H₂, CO background interference, and temperature-fluctuation conditions. The Pd–Cu sensor exhibited a good linear response over 0–500 ppm H₂, with a sensitivity of 0.0845 nm/ppm. Under a mixed atmosphere of 200 ppm H₂ and 500 ppm CO, the Pd–Cu sensor measured 198 ppm, whereas the pure Pd sensor measured 176 ppm, corresponding to relative errors of approximately 1% and 12%, respectively. In addition, the Pd–Cu sensor showed faster response/recovery behavior and better output stability after temperature compensation. These results indicate that, under the investigated conditions, the selected Pd–Cu-sensitive layer can effectively reduce CO-induced interference and improve the accuracy and stability of fiber-optic MEMS hydrogen sensing, supporting its feasibility for representative early-warning-related monitoring scenarios in energy storage batteries. Full article

Ball resonator optical fiber sensors (OFSs) can offer multiparameter sensing capability, but their non-periodic and low-finesse reflection spectra make conventional spectral demodulation unreliable. This work proposes two sensor configurations: (i) a ball resonator and (ii) a hybrid sensor integrating a Fabry–Pérot interferometer (FPI) with a ball resonator, and compares their performance for multiparameter physiological monitoring using the Karhunen–Loève transform (KLT). The sensors were evaluated for glucose concentration (0–3 mg/mL), temperature (20–55 °C), and pH (3–9) monitoring. The ball resonator sensor, paired with KLT, achieved high linearity across all measurands (R² = 0.989, 0.919, and 0.838 in response to glucose, temperature, and pH, respectively). The hybrid sensor exhibited a higher glucose sensitivity (6.15 a.u./(mg/mL)) compared to the ball resonator (3.77 a.u./(mg/mL)), resulting in limits of detection (LODs) of 2.53 mM and 4.19 mM, respectively. In contrast, the ball resonator sensor demonstrated better sensitivity for temperature and pH sensing. Furthermore, we present a comprehensive benchmarking framework of seven spectral demodulation methods for OFSs. The results demonstrated that KLT consistently provides robust demodulation performance and highlighted the potential of KLT for multiparameter physiological sensing applications. Full article

To address the need for high electrical insulation, strong immunity to electromagnetic interference, and miniaturized AC electrical-signal detection in complex electromagnetic environments, we propose and experimentally demonstrate a fiber-optic sensor based on a piezoelectric ceramic (PZT)-driven ring tapered-fiber resonator. The applied AC excitation is converted into periodic mechanical deformation through the inverse piezoelectric effect of the PZT, and the resulting strain modulates the resonator response, enabling optical demodulation of the input frequency and amplitude. A comprehensive figure of merit was introduced to optimize the tapered-fiber geometry, yielding an optimal waist diameter of approximately 10 μm. The sensor can effectively distinguish both single- and dual-frequency AC signals. Over the range of 50–500 Hz, the demodulated frequency agrees closely with the input frequency, with a linear fitting coefficient of 0.9999. At a fixed driving frequency of 250 Hz, the amplitude of the characteristic spectral peak increases nearly linearly with the input voltage amplitude, with a fitting coefficient of 0.9945. The device also exhibits good stability over 30–150 °C and during 70 h of continuous operation. With its simple structure, low cost, and strong immunity to electromagnetic interference, this sensor provides a practical solution for AC electrical-signal detection in complex environments. Full article

Accurate impact localization on spacecraft structural panels subjected to contact loading by on-orbit servicing robots is critical for real-time structural health monitoring (SHM), yet remains challenging due to heterogeneous elastic wave propagation in complex aluminum structures with stiffener ribs and bonded joints. Conventional Received Signal Strength Indicator (RSSI)-based weighted centroid methods rely on fixed path-loss exponents that cannot accommodate spatially varying wave attenuation, resulting in position-dependent localization errors that worsen significantly near structural discontinuities. This paper proposes a Crow Search Algorithm (CSA)-optimized adaptive weighted centroid algorithm using distributed Fiber Bragg Grating (FBG) sensors, featuring three principal innovations: (i) a novel FBG wavelength-shift-to-RSSI amplitude mapping derived from elastic wave attenuation theory, bridging optical fiber sensing with centroid localization; (ii) per-event online weight optimization via CSA that adapts sensor contributions to each individual impact’s strain-wave signature; and (iii) a multi-objective fitness function simultaneously optimizing localization accuracy, noise robustness, and temporal consistency. The proposed method is validated across 200 impact events distributed over five representative positions on a 1 m³ Al6061 satellite-like structure with 64 FBG sensors (8 × 8 grid, 125 mm pitch), under three Gaussian noise levels (σ = 1%, 3%, 5% of signal RMS), and benchmarked against classical weighted centroid (WC), PSO-WC, GA-WC, DE-WC, and GWO-WC using paired t-tests (p < 0.01). CSA-WC achieves a mean localization error of 4.63 mm—an 83.29% improvement over classical WC and the lowest error among all five compared algorithms—with an average computation time of 0.14 s per event, satisfying real-time monitoring requirements. Full article

Exhaled breath analysis offers a non-invasive route for metabolic monitoring and disease screening, but its practical implementation requires sensing platforms that combine high sensitivity, robustness, and simplicity. Here, we report an evanescent wave-excited fiber-optic surface-enhanced Raman scattering (SERS) sensor based on silver nanocubes (Ag NCs) assembled onto a fiber taper waist (FTW), and the design is further extended to an Ag/graphene oxide (GO) hybrid interface for enhanced gas detection. Finite element and finite-difference time-domain simulations were employed to optimize the FTW geometry and Ag NC dimensions for efficient evanescent-field excitation and plasmonic enhancement. The fabricated FTW-SERS probe achieved a minimum detectable concentration of 10⁻⁹ M for crystal violet, together with good linearity and a relative standard deviation below 5%. For gas sensing, ethanol and acetone vapors were detected down to 50 ppm using the Ag NC-based FTW-SERS probe. After introducing a 0.3 mg/mL GO functional layer, the minimum detectable concentrations of both analytes were further reduced to 25 ppm. In addition, proof-of-concept monitoring of exhaled ethanol after alcohol consumption revealed dynamic spectral changes consistent with ethanol metabolism. These results demonstrate the potential of evanescent wave-excited FTW-SERS probes for compact and sensitive breath-analysis applications. Full article

This paper presents a force sensor made of a compliant glass mechanism instrumented with a waveguide and a Bragg grating, measuring the reflected wavelength shift produced by the strain in the compliant element generated by the applied force. The compliant element geometry and material have been chosen for the sensor to be spliced or manufactured at the extremity of an optical fiber, enabling possible insertion of the instrument in the bronchial tree after embedding in a proper catheter. The context of this research is the mechanical discrimination between healthy and cancerous lung tissues based on their mechanical signature. The paper proposes a comprehensive study including the mechanical design of the structure and the optimization of the production parameters, thanks to an experimental parametric study. After experimental characterization of the mechanism stiffness, the optical response to a mechanical force is reproduced with two different samples on two different days (more than 25 repetitions). The conclusion is that a fair linear and repeatable response is observed (± 26 mN) for forces ranging from 0 to 250 mN. Full article

Tube boilers are extensively employed in oil and gas refineries, as well as in petroleum, energy, and power generation industries, where they serve critical functions in local steam-generation units and combined-cycle gas turbine (CCGT) plants. However, these boilers are prone to defects arising from waterside corrosion (e.g., thinning of U-bend tubes), fireside corrosion, and material degradation caused by stress or creeping. Among these issues, wall thinning of tube bends is particularly severe, as it results in localized metal loss, reduced structural integrity, and an elevated risk of tube rupture or failure under high-temperature and high-pressure operating conditions. Such failures can significantly compromise boiler safety and efficiency, potentially leading to forced outages, costly unplanned repairs, or catastrophic damage if not detected in time. The current condition-monitoring policy for U-bends relies on scheduled preventive maintenance and unscheduled corrective interventions. In practice, this involves randomly checking approximately 10–20% of the tubes through spot scanning, partial scanning, or full scanning, with repairs typically carried out only after an undetected failure occurs. Such maintenance strategies generally require plant shutdowns, making the process time-consuming, labor-intensive, and ultimately not cost-effective. This paper reviews existing solutions, technologies, and research addressing the problem, and introduces femtosecond laser micromachined fiber optic sensors as a transformative approach for real-time monitoring of wall thickness reduction in U-bend boiler tubes, thereby opening pathways for further research. Full article

To address the demand for underwater acoustic detection with hydrostatic pressure resistance, this paper proposes a fiber-optic Fabry–Perot (F-P) underwater acoustic sensor based on micro-electromechanical system (MEMS) technology. According to the F-P interference principle, the diaphragm deforms under acoustic pressure, inducing variations in the F-P cavity length which modulate the interference spectrum and enable the measurement of underwater acoustic signals. A sensing diaphragm with a composite structure consisting of a central boss and a micro-hole array is designed, which improves the optical signal quality while reducing the influence of the pressure difference between the inner and outer surfaces of the diaphragm on sensor operation. MEMS fabrication, computer numerical control (CNC) machining, and laser fusion splicing technologies are employed to achieve batch fabrication of the sensing units and adhesive-free integration of the sensor. Experimental results show that the proposed sensor exhibits a flat frequency response within ±1.5 dB over the range of 1 kHz to 10 kHz, with an average signal-to-noise ratio (SNR) of 86.35 dB. The sensitivity reaches −181.79 dB re 1 rad/μPa at 10 kHz, with a maximum nonlinearity of 0.48% F.S., a repeatability error of 0.15% F.S. and a dynamic range of 100.83 dB. The proposed sensor features miniaturization, high consistency, hydrostatic pressure self-balancing capability, and immunity to electromagnetic interference, providing a solid foundation for hydrostatic-pressure-resistant underwater acoustic measurements in deep-sea environments. Full article

This paper provides a comprehensive overview of the progress in fiber-optic gyroscope technology, covering 260 key studies of the last ten years. A critical comparative analysis of fiber-optic gyroscope with alternative inertial sensors (Micro-Electro-Mechanical Systems, Hemispherical Resonator Gyroscope, Ring Laser Gyroscope) has been carried out. Confirming the unique advantages of fiber-optic gyroscope for autonomous navigation. Fundamental limitations of accuracy are considered in detail: temperature drifts, polarization noise, and Rayleigh backscattering. Modern hardware methods for suppressing these errors, including the use of photonic crystal and hollow fibers (Air-Core/Hollow-Core), are also considered in this work. The central place in the review is occupied by the analysis of the technological paradigm shift from bulky discrete circuits to hybrid integrated photonics (Indium Phosphide, Silicon Nitride, Lithium Niobate) and hybrid architectures to reduce weight and size characteristics. The role of artificial intelligence (Deep Learning, Long Short-Term Memory) methods in nonlinear drift compensation and calibration is discussed. The usage of the Brillouin effect and optomechanics promising areas are outlined, necessary to create a new generation of navigation systems operating in the absence of Global Navigation Satellite Systems signals. Full article

Reliable detection of internal defects in pressure vessel structures remains essential for structural safety and condition-based maintenance. This study presents a low-complexity structural health monitoring framework based on fiber Bragg grating (FBG) sensing and multiresolution wavelet analysis for void detection in curved pressure vessel structures under guided wave excitation. Guided waves are introduced using piezoelectric actuators, while the FBG sensors capture the resulting strain-induced wavelength variations. Due to the limited bandwidth of the optical interrogator, the recorded signals represent the strain envelope response associated with guided wave interaction rather than the resolved ultrasonic carrier waveform. To characterize defect-induced changes, the acquired signals are analyzed using continuous wavelet transform (CWT) for time–frequency interpretation, and discrete wavelet transform (DWT) and wavelet packet transform (WPT) for energy-based multiresolution feature extraction. Experimental results show that void defects lead to consistent redistribution of wavelet-domain energy and increased non-stationarity in the measured strain responses. These trends are further supported by finite-element simulations, which reproduce similar energy redistribution patterns between intact and damaged cases. The proposed framework provides a physically interpretable and computationally efficient approach for defect detection using low-bandwidth FBG sensing, without reliance on high-speed acquisition or data-intensive learning models. The results demonstrate the feasibility of using energy-based multiresolution analysis of FBG strain signals for practical and scalable structural health monitoring of pressure vessel systems. Full article

Laser fiber-based collimation straightness measurement can eliminate the intrinsic drift of the laser source while offering a simple configuration and simultaneous measurement of straightness in two orthogonal directions. As a high-precision optoelectronic sensing method, it has been widely used for the measurement of straightness, parallelism, perpendicularity, and multi-degree-of-freedom geometric errors. However, two common issues remain in practical applications. One is the nonlinear response of the four-quadrant detector, the core position-sensitive sensor, which is caused by detector nonuniformity and the quasi-Gaussian distribution of the spot. The other is the degradation of measurement performance by atmospheric inhomogeneity and air turbulence along the optical path, particularly in long-distance measurements. To address these issues, a two-dimensional planar calibration method is first proposed to replace conventional one-dimensional linear calibration. A polynomial surface-fitting model is introduced to correct the nonlinear response and inter-axis coupling errors of the four-quadrant photoelectric sensor. Simulation and experimental results show that the proposed method significantly reduces the standard deviation of calibration residuals and improves measurement accuracy. In addition, based on our previously developed common-path beam-drift digital compensation method, comparative experiments were carried out on double-pass common-path and single-pass optical configurations employing corner-cube retroreflectors, and theoretical simulations were performed to analyze the influence of air-turbulence disturbances on measurement stability. Both theoretical and experimental results show that the double-pass common-path configuration exhibits more pronounced temporal drift. Therefore, a real-time digital compensation method for beam drift in long-distance single-pass common-path measurements is proposed. Experimental results demonstrate that the proposed method effectively suppresses drift induced by environmental air turbulence and thereby improving the accuracy and stability of long-travel geometric-error and related straightness measurement for machine-tool linear axes. Full article

Structural health monitoring (SHM) plays an increasingly important role in managing aging, safety-critical infrastructure under growing environmental and operational demands. In recent years, fiber-optic sensors (FOSs) have attracted significant attention for SHM applications due to their immunity to electromagnetic interference, durability in harsh environments, multiplexing capability, and suitability for both localized and fully distributed measurements. In parallel, advances in machine learning (ML) have enabled new approaches for extracting actionable insights from large, high-dimensional sensing datasets. This paper presents a systematic review of FOS-based SHM systems integrated with ML across civil, transportation, energy, marine, and aerospace infrastructures. Following PRISMA 2020 guidelines, peer-reviewed studies were identified and synthesized to examine sensing principles, deployment configurations, data characteristics, and learning-based analytical strategies. Fiber optic technologies are categorized into point-based, quasi-distributed, and fully distributed systems, and their capabilities for capturing strain, temperature, and spatiotemporal structural responses are critically evaluated. ML approaches are examined from a task-oriented perspective, including damage detection, localization, severity assessment, environmental compensation, and prognosis, with emphasis on the alignment between sensing configurations and appropriate learning paradigms. Key challenges remain, particularly regarding large data volumes, environmental variability, limited labeled damage datasets, model generalization, and system-level integration. Emerging directions such as physics-informed and hybrid learning, transfer learning, uncertainty-aware modeling, and integration with digital twins are discussed as pathways toward more robust and scalable SHM systems. By jointly addressing sensing physics and data-driven intelligence, this review provides a structured reference and practical roadmap for advancing intelligent FOS-based SHM in next-generation infrastructure. Full article

Mine rescue operations are frequently conducted in hazardous underground environments characterized by damaged infrastructure, unstable communications, heat stress, and hypoxia risk, all of which threaten the safety of rescue personnel. To address these challenges, this study proposes a prototype-oriented mine-rescue monitoring framework that combines a Wi-Fi/optical-fiber communication architecture with flexible wearable sensing modules for physiological monitoring. The communication design employs Wi-Fi for local wireless data aggregation and optical fiber for reliable long-distance backhaul to the surface command side. For wearable monitoring, two flexible sensing modules were developed: a temperature sensor based on a polyaniline/graphene–polyvinyl butyral composite film and a PPG-oriented flexible optoelectronic module based on an ITO/Ag/ITO multilayer transparent electrode structure. Experimental results show that the temperature sensor exhibits a clear temperature-dependent resistance response within the tested range, while the optoelectronic module demonstrates low sheet resistance and acceptable electrical continuity under repeated bending. These results provide preliminary support for combining hybrid underground communication architecture with flexible wearable sensing components in mine-rescue scenarios. However, the present work remains at the stage of architecture design and component-level validation, and full end-to-end system verification under simulated or field rescue conditions will be the focus of future studies. Full article

Vertical-External-Cavity Surface-Emitting Lasers (VECSELs) have gained significant attention over the past two decades due to their versatility in a wide range of photonic applications. This review focuses on VECSEL configurations for dual-wavelength emission, highlighting their use in high-resolution spectroscopy, terahertz (THz) generation, and advanced optical communication. We explore recent developments in VECSEL designs, including systems utilizing birefringent crystals for polarization-based frequency separation and configurations with dual-VECSEL chips or dual-gain regions within a single cavity. These two-wavelength VECSELs enable diverse operation modes, including narrow-linewidth, pulsed, multimode, and frequency-converted emission, with high-brightness output, excellent beam quality, and tunable wavelengths. Additionally, the review discusses advancements in dual-frequency VECSELs, with applications in LIDAR systems for environmental monitoring, highly stable optical clocks, and fiber sensors. We examine improvements in cavity design, semiconductor structures, and power stabilization, which have enhanced frequency stability and spectral purity, making VECSELs suitable for precision metrology and sensing applications. Full article

The detection of glucose is a critical aspect of healthcare and biomedical research, particularly for the management of diabetes mellitus. Among various sensing technologies, surface plasmon resonance (SPR)-based optical fiber sensors have emerged as a promising platform due to their high sensitivity, real-time monitoring capabilities, and miniaturization potential. This paper explores the development and application of a molecularly imprinted polymer (MIP)-coated eccentric core optical fiber SPR sensor for glucose concentration detection. The integration of MIP technology with SPR sensing enables enhanced specificity and selectivity towards glucose molecules, while the eccentric core structure of the optical fiber contributes to improved light–matter interaction and sensitivity. The amplitude sensitivities are calculated as 0.88771 [mmol/mL]⁻¹ for the 3% glucose solution, 0.35161 [mmol/mL]⁻¹ for the 3.5% solution, 0.20425 [mmol/mL]⁻¹ for the 4% glucose solution, 0.89041 [mmol/mL]⁻¹ for the 5% solution, and 1.55825 [mmol/mL]⁻¹ for the 7% solution. The proposed sensor exhibits a simple geometry and presents itself as a promising candidate for glucose solution concentration detection. Full article