Fiber interferometers are widely used in precision measurements, yet phase-noise suppression over the mHz-kHz band remains a key bottleneck. Here, a specialty hollow-core photonic bandgap fiber (HC-PBGF) is introduced as the sensing arm to reduce temperature-induced phase noise. Comparative measurements show that, relative to a solid-core polarization-maintaining fiber (PMF) interferometer, the HC-PBGF interferometer achieves an ∼18 dB reduction in phase-noise power spectral density (PSD) in the mHz-Hz band while maintaining an ∼7 dB advantage in the Hz-k Hz band, which is qualitatively consistent with the simplified theoretical prediction. These results support the development of HC-PBGF-based broadband low-noise fiber interferometry.

Enhancing the transverse magneto-optical Kerr effect (TMOKE) signal is crucial for improving magnetic field sensor performance. In this paper, a high-performance biosensing structure based on TMOKE is proposed. The strong coupling between guided mode resonance (GMR) and Surface Plasmon Resonance (SPR) is realized by combining metal materials with magnetic media skillfully. The strong coupling mechanism not only effectively enhances the electromagnetic field locality of the system, but also significantly improves the strength of the TMOKE signal. Through in-depth analysis of the critical coupling conditions and optimization of structural parameters, the system achieves a TMOKE response amplitude close to 1, which fully verifies the great potential of the strong coupling mechanism in enhancing the magneto-optical effect. Furthermore, compared to traditional SPR sensors with a figure of merit (FOM) of approximately 102 RIU-1, the proposed structure achieves an exceptionally high FOM of 103 RIU-1, greatly improving sensing performance. This breakthrough provides a novel approach for high-precision molecular detection under low-energy conditions, with significant applications in chemical analysis, biomedical sensing, and materials science.

This paper presents a novel plate-type fiber optic sensor (PT-FOS) designed for enhanced underwater detection. The sensor consists of a Mach-Zehnder interferometer (MZI), with the sensing arm featuring multiple multi-layer fiber optic coils (FOCs) adhered to a rectangular thin plate. This coils detect deformations caused by underwater acoustic waves, which are then used to reconstruct the wave information. Finite element analysis (FEA) demonstrates that the sensor achieves a sensitivity of up to 97152.93 rad/g, corresponding to a sound pressure sensitivity of -147.85 dB re rad/mu Pa@1Hz. Furthermore, experimental results further validate the sensor's significant response to low-frequency underwater acoustic signals, highlighting the potential of fiber optic technology in advancing underwater detection applications.

Multi-turn optical fiber coils, as the key sensing components of Fiber Optic Disc Accelerometers (FODAs), significantly affect the FODA performances due to their layered structure. This paper explores the strain distribution characteristics of the optical fiber coils by utilizing the inherent properties of the FODA, supported by Finite Element Method (FEM) and high-precision Optical Frequency Domain Reflectometry (OFDR). The results indicate that the simulation outcomes are largely consistent with the OFDR measurements, accurately reflecting the strain distribution within the optical fiber coils of the FODA. This analysis dose not requires additional external force application devices and carries no risk of damaging the FODA. Based on FEM, the simulation model is employed to optimize the existing structure, proposing a multi-turn optical fiber coil fabricated from ultra-fine diameter fiber. By altering the structure of optical fiber coil to make the internal strain distribution trend uniform, the sensitivity of the FODA is increased to approximately 150% of its original value.

Achieving high sensitivity and robust environmental stability simultaneously remains a significant challenge in sensor research. Optical Vernier structure, serving as an excellent tool for substantially boosting sensing sensitivity, has become a current research hotspot. However, while it greatly improves sensitivity, the deterioration of environmental stability is inevitable. In this article, we propose and experimentally validate a temperature sensor based on the common-path interferometer Vernier structure (CPI-VS) using polarization-maintaining fiber (PMF). This sensor not only demonstrates high sensitivity (45.18 nm/degrees C) and robust environmental stability (with a 90.8 % improvement), but also achieves a detection limit of 0.011 degrees C, surpassing both the single MZI (0.022 degrees C) and the conventional DPI-VS (0.030 degrees C). This sensing structure utilizes a single PMF based Mach-Zehnder interferometer (MZI) and integrates a Faraday rotation mirror (FRM) to enable two orthogonal polarized light components to propagate sequentially. Due to the Vernier effect, the sensor's sensitivity is enhanced about 3660 times compared to a single MZI by adjusting the ratio of the arm length to the arm length difference. Experimental results are consistent with theoretical simulations. Furthermore, the sensor design improves environmental stability by 90.8 %, addressing the traditional trade-off between sensitivity and stability in fiberoptic interferometers. This work offers a novel approach to the design and application of high-sensitivity, environmentally stable fiber-optic sensors.

The commonly used mandrel-type or disk-type fiber-optic accelerometers (DT-FOAs) are inherently limited in their capacity to detect low-frequency signals due to their structural characteristics. The fiber-optic coil (FOC), as the core sensing component of an interferometric FOA, plays a crucial role in determining the sensor's sensitivity through its strain distribution characteristics on the transducer plate. This article presents, for the first time, the novel introduction of noncircular FOCs (NC-FOCs), which are employed in the design of a rectangular thin-plate FOA and plate-tpye FOA (PT-FOA) to improve low-frequency detection performance. In this study, the finite element method (FEM) and tensor analysis theory are employed to establish a universal model for PT-FOA constructed with NC-FOCs. Sensors with FOCs of various shapes were designed, fabricated, and tested. Both theoretical and experimental results demonstrate that different shapes of FOCs can improve sensitivity by approximately 14.62%. The underlying mechanisms of these improvements are analyzed by studying the strain tensor distribution on the transducer plate. The proposed PT-FOA addresses the limitations of existing FOAs in low-frequency detection. The sensitivity enhancement method maintains the same resonant frequency and thermal noise levels while significantly improving the signal-to-noise ratio (SNR) and sensitivity of the sensor. This work provides a general modeling approach and valuable practical guidance for the design and optimization of high-sensitivity FOAs, with important implications for both research and application.

A closed-loop fiber optic accelerometer with wide bandwidth and high sensitivity based on electromagnetic feedback is proposed. Compared with the open-loop system, the bandwidth of 3 dB can be extended to about 210 Hz, which is increased by about 3.5 times, and the sensitivity is maintained at 72.97 dB re rad/g. At the same time, the sensor can also realize free bandwidth regulation to a certain extent to meet different application requirements.

Temperature cross-sensitivity, which especially performs complicatedly and severely in fiber-optic sensors composed of various materials, will significantly affect the stability and the accuracy of the parameter to be measured. Consequently, the polarization-multiplexed technology is introduced to separate the temperature and strain parameters, while a piecewise uniform compensation method is further proposed and employed to get rid of the nonlinear temperature effects in the fiber-optic vibration sensing unit (FOVSU). In the sensitive fiber coil (SFC) of the FOVSU, the solution interval of temperature coefficient is subdivided and employed for decoupling in different temperature ranges; then, the data are processed by splicing finally. The experimental results show that a suppression effect of temperature drift noise of 43 dB at 1 mHz is achieved under unidirectional self-cooling temperature conditions and 33 dB at 1 mHz under continuous temperature rise and fall conditions by using the piecewise method, which demonstrates that the performances in both situations are better than the original method using only one set of temperature coefficients. Therefore, the proposed new method could significantly reduce the temperature noise, leading to the testing accuracy and stability enhancement of FOVSUs.

Transverse magneto-optical Kerr effect (TMOKE) is widely used in many fields, such as materials science, magnetic research, and optoelectronics, which can provide a key theoretical basis for exploring the relationship between magnetic and optical properties of materials. In this article, we investigated the deposition of BIG:YIG nanograting arrays on SiO2/Si substrates and found that the system excited Bloch and magnetic dipole resonance modes, leading to significant TMOKE enhancement. The results show that the amplitude enhancement of these two modes reaches 0.7 and 0.4 in the visible and near infrared range, respectively, and the corresponding resonance linewidths are only 0.008 and 0.05 nm. By analyzing the influence of the change of the ambient refractive index on the sensing performance, it is found that the system has good sensitivity and high figure of merit (FOM). The sensitivity of mode 1 is 355 nm/RIU, FOM is up to 7x 10(4) RIU -1 , and the detection limit is as low as 0.0000563 RIU. The sensitivity of mode 2 is 260 nm/RIU, FOM is up to 5x 10(3) RIU (-1) , and the detection limit is as low as 0.0000769 RIU. This dual-channel highly sensitive sensor will provide high-precision, real-time multiparameter monitoring solutions for multiple fields and promote the intelligent development of environmental, medical, chemical, and industrial fields. In addition, compared with the traditional all-metal structure or the hybrid metaldielectric structure, the all-dielectric nanograting array effectively avoids the metal-induced ohmic losses, thus significantly reducing the energy loss and improving the detection performance of the system.

A control method of electromagnetic feedback is proposed for adjusting frequency response characteristics of fiber optic accelerometers, which could expand the flat working bandwidth and enhance performance consistency. The proof sensor employs an open-loop disc-type vibration pickup structure, cascaded with an electromagnetic feedback control unit. A proportional-differential control algorithm is utilized to generate the feedback signal, which ultimately acts on the input side of the sensor. Experimental results show that the 3 dB bandwidth of the constructed closed-loop system is expanded to approximately 210 Hz, more than 3.5 times that of the open-loop system, while maintaining a sensitivity of 72.97 dB re rad/g. Furthermore, the regulated closed-loop systems exhibit a significantly reduced response deviation, compared to the open-loop systems with fluctuating response characteristics due to fabrication errors.

Loose fasteners in railway tracks present a potential safety concern for train operations, especially when fasteners at sharp curves become loosened or when multiple consecutive fasteners are loosened. Traditional inspection methods are inefficient due to the large number of fasteners along the rail. This study introduces Fiber-optic based Distributed Acoustic Sensing (DAS) technology for real-time health monitoring of rail track, and proposes a DAS-based framework including both supervised and unsupervised learning methods for detecting loosened fasteners. In the supervised approach, a DAS signal anomaly detection (DSAD) model is proposed to directly predict the torque applied to the fasteners. Conversely, the unsupervised method employs a DAS signal anomaly detection Variational Autoencoder (DSAD-VAE) model, which evaluates the difference between the reconstructed and input signals to quantitatively assess the extent of loosening of rail fasteners. In the laboratory track tests, the DSAD model achieves an average prediction accuracy of about 1 N m per bolt, while the DSAD-VAE model attains an impressive F1-score of 0.9 for classification. Furthermore, during field tests conducted on a subway track, the DSAD model achieves a F1-score of 0.9917 for fastener loosening classification, while the DSAD-VAE model achieves 100% accuracy in unsupervised monitoring of fastener anomalies.

Effective health monitoring of concrete structures is vital in structural and geotechnical engineering, especially for internal monitoring in harsh environments. This article presents and validates a solution for distributed fiber optic sensing (DFOS) using Brillouin optical frequency-domain analysis (BOFDA) technology for monitoring the internal strain throughout the life cycle of common concrete slabs. The principle and sensing mechanism of BOFDA are briefly introduced and analyzed. A well-designed and deployed fiber under test (FUT) layout is utilized to accurately capture the internal strain distribution of a concrete slab. Besides, fiber Bragg grating (FBG) sensors and a thermocouple probe are incorporated for point strain reference and global temperature compensation. This paper presents a comprehensive monitoring method of concrete slabs throughout their entire life cycle. The monitoring process covers the preparation, pouring, curing, corrosion, and loading stages. Our experimental results demonstrate the feasibility of holistically monitoring strain distribution in concrete slabs over their lifetime. Additionally, post-processing of the data enables tracking of strain evolution at specific sensor nodes of interest. Furthermore, our study includes an extreme loading scenario, allowing examination of the strain variation process at rebars and key nodes. The strain distribution patterns observed in the experiment align with the finite element simulation results. These findings provide valuable guidance for crack prediction and structural health monitoring (SHM) of concrete slabs. The proposed scheme offers a unique and highly precise solution for full life-cycle SHM capable of functioning effectively in harsh environments such as energization and saltwater corrosion, thereby expanding its potential applications.

Achieving precise and reliable automated pavement crack detection using deep learning techniques is vital for intelligent pavement maintenance. This study proposes CrackDiffusion, an enhanced-supervised detection framework for pavement crack, combining two supervised and unsupervised stages. In Stage 1, a multi-blur-based cold diffusion anomaly detection model is proposed, which transforms crack-containing images into crack-free images, while simultaneously extracting pixel-level crack features using the Structural Similarity Index measure (SSIM). In Stage 2, an improved supervised U-Net segmentation model enhances accuracy and robustness by building upon the unsupervised results from Stage 1, ultimately producing highly accurate pixel-level segmentation results for cracks. On four public datasets, both the proposed multi-blur-based cold diffusion model and the comprehensive CrackDiffusion framework attained the highest Intersection over Union (IoU) scores, surpassing the IoU scores of the current state-of-the-practice unsupervised and supervised segmentation models.

We propose and demonstrate an accurate demodulation method for fiber-optic interferometric sensors (FOISs) by utilizing an expanded free spectral range (EFSR). Unlike conventional demodulation schemes, this method selects a pair of resonant wavelengths (peaks or dips) with an interval of multiple free spectral ranges (FSRs) to determine the optical path difference (OPD) of the FOIS. This demodulation method significantly improves the measurement accuracy of the FOIS while maintaining a fast processing speed. The feasibility of the proposed method is experimentally demonstrated by our recently developed fiber-optic piezometer using a 178- $\mu \text{m}$ -gap air extrinsic Fabry–Perot interferometer (EFPI). Liquid level measurement in the range of 0–90 cm with a step of 15 cm is conducted with this method, and the experimental results demonstrate improved performance in terms of linearity, standard error (SE), and resolution. The measurement resolution increases significantly from 8.57 to 1.48 cm when the EFSR orders vary from 1, 4, 8, 12, 16, to 20. To further validate the proposed method, the measurement in the range of 0–24 cm with a step of 4 cm is performed for comparison, and the resolution is exponentially improved from a failed state to as high as 0.41 cm. Furthermore, five sets of historical data are chosen to establish regression models, and the results are consistent with the rest 14 sets of measured data. The proposed demodulation method is precise, rapid, and versatile, which would be useful in the further development and application of FOISs.

Entangled qudits, the high-dimensional entangled states, play an important role in the study of quantum information. How to prepare entangled qudits in an efficient and easy-to-operate manner is still a challenge in quantum technology. Here, we demonstrate a method to engineer frequency entangled qudits in a spontaneous parametric downconversion process. The proposal employs an angle-dependent phase-matching condition in a nonlinear crystal, which forms a classical-quantum mapping between the spatial (pump) and spectral (biphotons) degrees of freedom. In particular, the pump profile is separated into several bins in the spatial domain, and thus shapes the down-converted biphotons into discrete frequency modes in the joint spectral space. Our approach provides a feasible and efficient method to prepare a high-dimensional frequency entangled state. As an experimental demonstration, we generate a three-dimensional entangled state by using a homemade variable slit mask.

We propose, what we believe to be, a novel method for high temperature sensing calibration based on the mechanism of alterable interferential fineness in Bragg hollow core fiber (BHCF). To verify the proof-of-concept, the fabricated sensing structure is sandwiched by two sections with different length of BHCF. Two interferential fineness fringes dominate the transmission spectrum, where the high-fineness fringes formed by anti-resonant reflecting optical waveguide (ARROW) plays the role for high temperature measurement. Meanwhile, the low-fineness fringes induced by short Fabry-Perot (F-P) cavity are exploited as temperature calibration. The experimental results show that the ARROW mechanism-based temperature sensitivity can reach 26.03 pm/°C, and the intrinsic temperature sensitivity of BHCF is 1.02 pm/°C. Here, the relatively lower magnitude of the temperature sensitivity is considered as the standard value since it merely relies on the material properties of silicon. Additionally, a large dynamic temperature range from 100 °C to 800 °C presents linear response of the proposed sensing structure, which may shine the light on the sensing applications in the harsh environment.

As the preventive maintenance paradigm transfers to condition-based maintenance, deformation monitoring has become a fundamental system capacity in aerospace engineering. In this study, a novel shape sensing method is proposed for accurate and efficient reconstruction of full-field deformation of thin shell structures from discrete strain measurements. Firstly, a flexible isogeometric approach based on the geometry-independent field approximation is developed for characterizing the geometric and physical domains, which fully unlocks the potential of local refinement while preserving the original exact geometry without re-parameterization. On this basis, a posteriori error estimation algorithm is put forward to automatically drive the adaptive refinement procedure, reducing the discretization error with a fast convergence rate. Subsequently, according to the Kirchhoff-Love theory and the least-squares variational principle, an isogeometric inverse-shell element is created to integrate the inherent advantages of adaptive isogeometric analysis with excellent shape-sensing capabilities of the inverse finite element method. Moreover, a smoothing technique is applied to replenish strain data into each inverse shell element, by which the compatibility between the interpolated and measured strain components is also enforced. Finally, the excellent accuracy and efficiency of the proposed deformation reconstruction framework are verified using both experimental and numerical strain data for two thin-shell spaceborne antennas.

To accurately unwrap the high-order orbital angular momentum (OAM) for multiplexed vortex beams is a challenge. In this work, over ±160 order OAM topological charges have been unwrapped in multiplexed optical links. Optical imaging based discrepancy identification enables the multiplexed OAM modes separating in physics, and the intelligent pattern recognition further promotes its unwrapping in numerical domain. Particularly, the combination of annular phase grating and auxiliary beams features compound spiral stripes, which paves the way for optical intensity recognition with low-complexity and high-commonality. Moreover, the spiral direction characterizes the symbol of the OAM states, which dramatically broadens the amount of multiplexed links. Here, optical separating means assisted by intelligent pattern recognition opens up a new route to high-speed and large-capacity optical communication, which may shed new light on 6G application.

In comparison to current techniques, optical fiber sensors (OFS) for structural health monitoring (SHM) of steel fibre reinforced concrete (SFRC) tunnel lining segments is an emerging technology that could enhance tunnel safety and reliability. However, the utilizing many measurement techniques in a single OFS technology has pros and cons, making it difficult to meet the demands for a comprehensive and reliable assessment for long-term monitoring inside tunnels. We present comprehensive OFS system for strain monitoring inside concrete tunnel lining segments. The system involves distributed optical fiber sensing (DOFS) cable, fiber Bragg grating (FBG) sensors, and chirped fiber Bragg grating (CFBG) sensors. The proposed system is particularly useful for high-risk or difficult-to-access locations, such as inside tunnel structures. We provide the deployment design after introducing the sensing principle of the system. To validate its effectiveness and reliability, we conduct a scaled-down laboratory experiment to evaluate the strain behavior. The proposed comprehensive OFS system accurately captures the strain evolution over time in various stages of tunnel lining segments, including casting, curing, loading, and even after failure. This system demonstrates high-resolution, and reliable monitoring of internal strain in tunnel lining segments, making it suitable for practical application in full-scale and long-term SHM during the construction and operation stages of shield tunnels with connection expansion for segments.