Search Results (3,466)

A Q-switched pulsed laser based on a coupled 7-core Yb-doped fiber with a cavity based on a fiber Bragg grating array has been demonstrated with a maximum energy of microsecond pulses up to 15 μJ at a 1 kHz repetition rate. The lasing spectrum is hybridized so that the laser line maxima of each core are nearly the same, having a negligible spread relative to each other, which is much lower than the wavelength shifts between individual FBGs in the cores. At the same time, the generated power is nearly the same in all the cores. However, when increasing the power beyond the stimulated Raman scattering threshold, the supermodes are destroyed so that the spectra in the cores become increasingly different and less stable, and the output power is mainly concentrated in one of the cores, whereas the pulse shortens significantly to a sub-microsecond duration (300 ns), with damped oscillations appearing at the beginning. The new regimes we demonstrated of the multicore fiber laser are promising for creating powerful pulsed radiation sources with a narrow spectrum. Full article

This study presents an experimental and numerical investigation on the impact of embedded fiber optic sensors on the mechanical properties, like tensile, compression, bending and compression-after-impact properties, and sensing performances of intelligent composites. The influence by different volume fractions of embedded fiber optics on the mechanical properties was revealed. Combined with finite element simulations, the effect of embedded sensors on the basic mechanical properties of composite materials was obtained. The sensing performance of the embedded fiber Bragg grating (FBG) sensors was validated through comparison with conventional strain gauges. Full article

This study demonstrates single-channel fiber Bragg grating (FBG) sensing for relative vibration-state monitoring of a motor–support system under angle-dependent boundary conditions. A packaged FBG accelerometer-type sensing unit was mounted on the motor–support structure, and the reflected Bragg wavelength was recorded as a one-dimensional optical vibration response. Because the sensor was installed away from the rotating shaft, the measured wavelength fluctuation was interpreted as a coupled vibration-sensitive response of the motor, fixture, sensor package, bonding condition, and changing boundary state, rather than as a calibrated shaft speed or absolute acceleration signal. Adaptive variational mode decomposition (AVMD) was applied to track the time-varying narrowband spectral-response trajectory of the Bragg-wavelength signal. In parallel, raw wavelength windows were supplied to LSTM, 1D-CNN, and CNN–LSTM autoencoders to evaluate waveform departures from learned nominal fixed-angle behavior. The fixed-angle results showed stable but distinguishable optical vibration responses under different boundary states, whereas the dynamic angle-transition records produced local trajectory changes and alarm-candidate intervals. Baseline and autoencoder comparisons further clarified the trade-off between transition coverage and false-alarm tendency. The RMS threshold baseline was more sensitive to transition-related amplitude changes but produced more false alarms, whereas the CNN–LSTM autoencoder provided the most selective response among the tested autoencoder branches. The results are interpreted as task-specific evidence for relative vibration-state transition monitoring rather than as general motor fault diagnosis. Overall, the framework demonstrates a compact FBG-based route for relative vibration-state transition monitoring when speed references, dense sensor layouts, and labeled fault data are unavailable. Full article

In this work, plasmonic photoconductive antenna (PCA) structures with different grating-width and gap configurations were numerically investigated to evaluate their influence on transient-current generation and terahertz (THz) emission performance. Two geometrical scaling strategies were considered: a fixed-gap configuration with a constant 100 nm photoconductive gap and a proportional-gap configuration in which the gap size was equal to the grating width. Three-dimensional finite element method (FEM) simulations were performed to analyze transient carrier dynamics, THz pulse electric-field behavior, and frequency-domain spectral response under 800 nm optical excitation. The results demonstrate that reducing the inter-grating gap enhances plasmonic near-field confinement and carrier localization near the metal–semiconductor interface, leading to stronger transient-current responses and enhanced THz characteristics. Spatial field and carrier-distribution analyses further confirmed improved electric-field localization and carrier confinement for the fixed-gap structures. In addition, voltage-dependent investigations showed that increasing the applied bias voltage strengthens carrier acceleration and enhances the simulated THz response within the investigated operating range. The results further demonstrate that the observed enhancement is governed not only by grating periodicity but also by the grating-width/gap-size ratio, highlighting the importance of geometrical fill-factor optimization. Polarization-dependent simulations confirmed the plasmonic origin of the enhanced transient-current generation and THz emission. These findings demonstrate that optimal THz performance arises from a balanced interplay between plasmonic field localization, optical absorption, and carrier-transport dynamics, providing design guidelines for the optimization of plasmonic THz PCAs. Full article

Precise monitoring of vibration signals is crucial for early fault warning and localization in industrial applications. Traditional electromagnetic accelerometers are often unsuitable for harsh environments characterized by high temperatures, high pressures, and strong electromagnetic fields. Fiber Bragg grating (FBG) accelerometers have become a major research topic in this field due to their unique advantages, including resistance to high temperature and pressure, immunity to electromagnetic interference, and ease of wavelength division multiplexing. This paper provides a systematic review of FBG accelerometers, covering their fundamental principles, classification, performance enhancement strategies, and applications. We focus on reviewing the research progress of FBG accelerometers from two main aspects, single-axis and multi-dimensional vector types, and offer an outlook on future development to provide a reference for the research and application of FBG accelerometers. Full article

In this paper, a comprehensive investigation into the single-mode capability of curved sapphire fiber is performed, ranging from theoretical simulation to experimental verification. The equivalent refractive index theoretical model for curved sapphire fiber is proposed based on stress–optic effects and the conformal mapping technique. According to the finite element method, when the radius of curvature is 0.02 m, the curved losses’ difference between high-order modes and the fundamental mode is as high as five orders of magnitude, demonstrating the best single-mode potential. In addition, the curving experiments of sapphire fiber and sapphire fiber Bragg grating are completed. The transmission spectrum of the curved sapphire fiber with a curving radius of 0.02 m is the closest to that of the single-mode fiber. As for curved sapphire fiber Bragg grating (CSFBG), the 3 dB bandwidth of reflection spectrum with the same radius of curvature is also the smallest, with a value of 3.7 nm. Furthermore, the temperature performance of the proposed CSFBG is measured from 22 °C to 1600 °C. The sensitivity is 37.88 pm/°C (@1600 °C), and the measurement accuracy is ±2.98 °C. This study provides theoretical support for single-mode signal transmission of curved sapphire fibers and facilitates high-precision sensing applications under extreme high-temperature conditions. Full article

Stable control of the main combustion chamber temperature is critical for pollutant emission compliance, energy recovery, and equipment longevity in municipal solid waste incineration (MSWI). However, the response delays from manipulated variables such as primary air, secondary air, and feed rate to the furnace temperature span from seconds to tens of minutes, and a uniform-delay assumption is inadequate to characterize the true response lag. Moreover, without an action-smoothing constraint, optimizers tend to produce abrupt control commands that destabilize the temperature trajectory. Using real industrial distributed control system (DCS) data from a full-scale grate furnace, this paper develops a prediction–decision collaborative control framework. In the prediction module, mutual information (MI) is used to identify the optimal delay of each manipulated variable separately, and the time-aligned manipulated variables together with a low-order autoregressive component serve as input to XGBoost and yield a prediction RMSE of 6.85 °C with an $R^2$ of 0.9845. In the decision module, a normalized smoothing penalty is incorporated into the fitness function of particle swarm optimization (PSO) to constrain the step-to-step variation in manipulated variables. Offline predictor-in-the-loop simulation on the test set shows that, compared with a multi-loop PID controller, the proposed method reduces the standard deviation of the furnace temperature tracking error by about 35% (from 5.80 °C to 3.80 °C), and lowers the mean tracking error to 3.65 °C while improving actuator smoothness over both unconstrained PSO and a genetic algorithm. The framework provides a collaborative-control design for pre-deployment evaluation of data-driven controllers in MSWI operation. Full article

We propose a time-delay signature suppressed broadband chaotic (TSBC) carrier generation scheme and theoretically investigate its performance in a dual-polarization bidirectional chaotic communication system based on synchronized vertical-cavity surface-emitting lasers (VCSELs). The TSBC scheme is implemented by combining fiber Bragg grating (FBG) feedback with an external electro-optic (EO) phase modulation loop to introduce synergistic nonlinear perturbations. The results demonstrate that the proposed TSBC scheme effectively suppresses the time-delay signature (TDS) to less than 0.03 while significantly enhancing the chaotic carrier bandwidth to over 23 GHz for each polarization channel. Meanwhile, high-quality chaotic synchronization can be achieved with laser parameter mismatches of approximately 30%. Finally, an aggregated 46 Gbit/s dual-polarization bidirectional chaotic transmission is demonstrated, which confirms the effectiveness and the potential of the TSBC dual-polarization bidirectional scheme for secure optical communication applications. Full article

Accurate state-of-charge (SOC) estimation is essential for the safe and efficient operation of lithium-ion batteries. However, the weak voltage observability of lithium iron phosphate (LFP) batteries within the voltage plateau region limits the accuracy of conventional voltage-based methods. To address this issue, an electro–mechanical information fusion framework for SOC estimation is proposed. Fiber Bragg grating (FBG) sensors were employed to simultaneously measure the surface strain and temperature of prismatic LFP batteries. Experimental results showed that the strain signal exhibited a stronger correlation with SOC than the voltage signal, with an average absolute correlation coefficient of 0.92. A Thevenin equivalent circuit model combined with an adaptive forgetting factor recursive least squares (AFFRLS) algorithm was established for online voltage modeling, while a Mamba-based strain model was developed to capture the nonlinear temporal relationship between multidimensional sensing data and battery strain. The two models were further integrated with adaptive unscented Kalman filters (AUKFs) and fused through a dual-layer adaptive weighting strategy. Experimental results under the five operating conditions considered in this study demonstrated that the proposed method achieved average RMSE and MAE values of 0.98% and 0.80%, respectively, outperforming standalone voltage- and strain-based methods. Full article

In this study, we present a thermal-aware design of a compact hybrid plasmonic grating (HPG) TE-pass polarizer on X-cut lithium niobate on insulator (LNOI) for fiber-optic gyroscopes (FOGs). In a three-dimensional simulation, the optimization of the trapezoidal sidewall angle (θ = 78°) and the thickness of the Ag grating (13 nm) yield a polarization extinction ratio of 36.2 dB at 1550 nm (with a peak of 41.4 dB at 1548 nm) within a sub-10 μm grating length. This represents a ~3–8 dB improvement over prior LNOI HPG polarizers at the same footprint. A multiphysics thermo-optic analysis over the wide industrial FOG envelope (from −45 to +85 °C) demonstrates that the operating-wavelength polarization extinction ratio remains within the range of 24.7–36.2 dB across the entire 130 K span (worst case 24.7 dB at −25 °C), constrained solely by a modest 10 pm/K Bragg detuning stemming from the pronounced (~5) thermo-optic anisotropy of LN. The insertion loss exhibits a negligible drift of merely 0.73 dB. A fabrication tolerance study identified the Ag thickness as the predominant budgetary constraint (±1 nm tolerance, PER dropping ~10 dB at the resonance edge), while the ridge width and oxide buffer demonstrated comparatively greater flexibility. The device, therefore, fulfills the criteria for FOG-grade polarization suppression across most of the operational temperature range. The −25 °C point is established at the 25 dB threshold, thereby providing concrete design guidelines for ensuring environmentally stable on-chip polarization control on LNOI. Full article

This study introduces an Electronically Controlled Root Crop Processor, a compact, Arduino-powered simulator designed to transform hands-on learning for TVET students. Built with locally available materials, it seamlessly integrates grating and juice extraction while prioritizing safety, ergonomics, and user-friendly operation. Experts rated the prototype highly for functionality and usability, with ergonomics scoring 3.96, while aesthetics and modularity scored 3.83, highlighting areas for refinement. By bridging classroom theory and practical skills, the processor offers an interactive, real-world food processing experience, empowering learners to develop technical competencies efficiently in laboratory settings. Full article

Surface plasmon resonance (SPR) is a key tool for quantifying biomolecular interactions, and its use in studying interacting components outside cellular systems is well-established. Over the past 20–25 years, cell-based SPR techniques have emerged, with the promise of precise detection of molecular interactions within their normal physiological environment. Research on a wide variety of biological samples, which requires the detection of numerous parameters, has led to the development of a broad range of SPR techniques. This review aims to trace the chronological development of these techniques and the factors that have driven them. In this context, particular focus is given to grating-coupled SPR applied to cell assays. Its specific capabilities are examined, and the respective advantages and disadvantages of other SPR techniques are discussed based on the results obtained from studying specific biological objects. Finally, we venture to predict the promising SPR techniques, as well as the areas of application in which significant results can be expected. Full article

Surface-emitting distributed-feedback (SE-DFB) semiconductor lasers based on second-order gratings face a fundamental triple constraint: the spatial co-location of gain, grating feedback, and vertical radiation functions limits single-mode selectivity, surface extraction efficiency, and far-field beam quality simultaneously. We propose a quasi-parity-time (PT)-symmetric SE-DFB laser with separated gain and radiating-grating sections. In this design, the electrically injected gain section and the passive second-order grating section are placed in different regions along the cavity axis, thereby separating electrical injection from surface emission without epitaxial regrowth. Coupled-mode theory and two-dimensional finite-element simulations demonstrate that the resulting longitudinal non-Hermitian gain–loss asymmetry produces spatial-overlap-dependent threshold discrimination, enabling an isolated low-threshold lasing branch that remains separated from competing cavity modes over the investigated pump-parameter range. Under the HR–AR boundary condition, the proposed design achieves a threshold gain margin of $\mathsf{\Delta }g=12.4$${\mathrm{c}\mathrm{m}}^{-1}$, more than six times that of a conventional HR–AR DFB benchmark considered here, together with an upward surface extraction efficiency of 23.4% obtained from 2D FEM simulations. A simplified steady-state rate-equation estimate further suggests that the increased threshold margin can support strong side-mode suppression. The design imposes no regrowth requirement and is fully compatible with standard single-growth InP ridge-waveguide fabrication. Full article

Structural health monitoring (SHM) is a component of modern civil engineering. This review analyzes the integration of sensing technologies and artificial-intelligence-based methods for damage detection, localization, classification, prognosis, and anomaly detection in buildings and civil infrastructure. The database search covered Web of Science (WoS), Scopus, and IEEE Xplore for the period 1 January 2020–31 December 2025. The initial records were 292 in WoS, 311 in Scopus, and 338 in IEEE Xplore; after applying the AI-related search constraint, the corresponding AI-SHM corpora were 71, 79, and 139 records, respectively. The combined screening and eligibility workflow produced 31 open-access studies for detailed qualitative analysis, while the task-specific performance tables synthesize the subset of studies for which the sensor type, AI model, SHM task, validation context, and performance metrics were explicitly reported. The review, therefore, interprets reported performance by SHM task and sensor modality, rather than treating heterogeneous metrics as directly comparable across different datasets and experimental conditions. The results indicate that high values reported for accelerometer-, fiber-optic-, piezoelectric transducer-, and vision-based systems are mainly obtained under controlled, benchmark, simulated, or study-specific validation conditions. Consequently, robustness, transferability to operational structures, uncertainty quantification, sensor-network design, and integration with Physics-Informed Machine Learning and Digital Twin technologies remain central research needs. Full article

Structural health monitoring (SHM) of fibre-reinforced composites requires a health indicator that is monotonically non-decreasing under the standard SHM assumption that no self-healing or maintenance-induced restoration event is active, derived from heterogeneous sliding-window observations of acoustic emission, strain, and fibre Bragg grating channels, with only the failure timestamp available per specimen. Conventional endpoint-supervised regressors attain high rank correlation with normalised life but produce jagged, non-monotone trajectories of limited engineering value. A method named SAMS-Net (Smoothness-Anchored Monotone Neural Differential Equation Network) is developed, in which a neural differential equation backbone is anchored by a two-level Pool-Adjacent-Violators (PAV) projection. A within-window projection is applied during training with a straight-through gradient, and an across-window projection is applied at inference, yielding a globally non-decreasing health indicator. A smoothness-stratified two-phase training schedule first trains on specimens whose per-specimen median local-smoothness coefficient exceeds 0.5, then fine-tunes on the full set. Across the present seventeen-specimen open-hole carbon-fibre dataset spanning two stress levels and six leave-one-specimen-out and cross-condition scenarios, SAMS-Net wins on every scenario on the canonical Prognostics and Health Management (PHM) Composite of monotonicity, trendability, and robustness, with margins of 0.22 to 0.48 against the strongest baseline, reproducible across three random seeds. Ablation reveals that the operative mechanism is the two-level PAV projection rather than the stochastic differential equation (SDE) inductive bias. A new control experiment in which the across-window PAV projection is applied at inference to the strongest baselines confirms that the projection accounts for a substantial share of the SAMS-Net margin, while the within-window training-time projection and a globally consistent prognosability metric retain a SAMS-Net advantage. Cross-site or cross-material transferability remains to be established in future work. Full article