Bragg Grating Research Articles

Federated learning-based wavelength demodulation system for multi-point distributed multi-peak FBG sensors

Machine learning-based demodulation of multi-peak fiber Bragg grating (FBG) sensors has been extensively studied, demonstrating superior performance compared to conventional algorithms because it can neglect potential physical constraints. As the number of real-world monitoring points increases, the volume of fiber-optic sensing data grows exponentially. This necessitates aggregating data from various regions (e.g., via Wi-Fi), unlike traditional single-point monitoring, which challenges server storage capacity and communication efficiency. To address these issues, this paper proposes a federated learning (FL)-based framework for efficient wavelength demodulation of multi-peak FBGs in multipoint monitoring. Specifically, an arrayed waveguide grating (AWG) with multiplexing capability is employed at different monitoring points to convert spectral features into multi-channel transmission intensities, serving as training data for local models. Subsequently, the local model parameters, trained independently at each point, are uploaded to a central server to derive the optimal global model for demodulation across different monitoring points. The proposed demodulation framework is validated through stress demodulation experiments on multi-peak FBG sensors. Experimental results indicate strong multi-peak extraction performance with a demodulation error of ±0.64 pm. Additionally, the method demonstrates excellent applicability for generating high-precision global demodulation models through multi-node cooperative work under various scenarios.

Phase-Shifted Fiber Bragg Grating by Selective Pitch Slicing

This paper presents a new type of phase-shifted Fiber Bragg Grating (FBG): the sliced-FBG (SFBG). The fabrication process involves cutting a standard FBG inside its grating region. As a result, the last grating pitch is shorter than the others. The optical output signal consists of the overlap between the FBG reflection and the reflection at the fiber-cleaved tip. This new fiber optic device has been studied as a vibration sensor, allowing for the characterization of this sensor in the frequency range of 150 Hz to 70 kHz. How the phase shift in the FBG can be controlled by changing the length of the last pitch is also shown. This device can be used as a filter and a sensing element. As a sensing element, we will demonstrate its application as a vibration sensor that can be utilized in various applications, particularly in monitoring mechanical structures.

Large Range Curvature Measurement Using FBGs in Two-Core Fiber with Protective Coating

In this work, we propose a fiber Bragg grating (FBG)-based sensor for curvature measurements. Two gratings are inscribed through the protective coating in a specialty optical fiber using focused femtosecond laser pulses and point-by-point direct writing technology. One grating is inscribed on the central core adjacent to an air channel, while the other is inscribed on the eccentric core. The bending characteristics of the two-core fiber strongly depend on the bending direction due to the asymmetry of the fiber cores. A bending sensitivity of 58 pm/m−1 is achieved by the FBG in the eccentric fiber core over the curvature range of 0–50 m−1 . Temperature and humidity cross-sensitivity could be significantly reduced by analyzing the differences in peak shifts between the two gratings. The sensor features a large sensing range and good robustness due to the presence of its protective buffer coating, which makes it a good candidate for curvature sensing in engineering fields.

Real-time optical fibre near-infrared chromatic dispersion analyser using collocated optical fibre gratings

We present what we believe to be a novel optical fibre device for real-time measurements of near-infrared chromatic dispersion of a liquid medium from 1100 nm to 1700 nm. This inline optical fibre chromatic dispersion analyser is based upon collocated fibre long-period gratings written adjacently in the core by femtosecond laser inscription yielding 8 attenuation bands associated with different cladding modes, yielding 8 independent measurements. This fibre device is tested on a series of chemical compounds associated with wines. The results for each compound yielded distinctive chromatic responses. A machine learning pipeline was developed that successfully clustered and classified spectral responses of the different chemicals to illustrate the distinctive responses. The limits of detection for these fibre devices ranged from 1×10−3 to 6×10−5 mol/L for the compounds associated with wines, demonstrating the potential usefulness of an optical fibre chromatic dispersion analyser is capable of monitoring in real-time effective chromatic dispersion that is not offered by any current technology.

A study on sleep posture analysis using fibre bragg grating arrays based mattress.

Prolonged sleeping postures or unusual postures can lead to the development of various ailments such as subacromial impingement syndrome, sleep paralysis in the elderly, nocturnal gastroesophageal reflux, sore development, etc. Fibre Bragg Gratings (a variety of optical sensors) have gained huge popularity due to their small size, higher sensitivity and responsivity, and encapsulation flexibilities. However, in the present study, FBG Arrays (two FBGs with 10mm space between them) are employed as they are advantageous in terms of data collection, mitigating sensor location effects, and multiplexing features. In this work, Liquid silicone encapsulated FBG arrays are placed in the head (E), shoulder (C, D), and lower half body (A, B) region for analyzing the strain patterns generated by different sleeping postures namely, Supine (P1), Left Fetus (P2), Right Fetus (P3), and Over stomach (P4). These strain patterns were analyzed in two ways, combined (averaging the data from each FBG of the array) and Individual (data from each FBG was analyzed separately). Both analyses suggested that the FBGs in the arrays responded swiftly to the strain changes that occurred due to changes in sleeping postures. 3-D histograms were utilized to track the strain changes and analyze different sleeping postures. A discussion regarding closely related postures and long hour monitoring has also been included. Arrays in the lower half (A, B) and shoulder (C, D) regions proved to be pivotal in discriminating body postures. The average standard deviation of strain for the different arrays was in the range of 0.1 to 0.19 suggesting the reliable and appreciable strain-handling capabilities of the Liquid silicone encapsulated arrays.&#xD.

Multi-Beam Surveying Ocean Exploration Model and Applications

With the development of artificial intelligence, fiber Bragg grating (FBG) sensing technology has garnered increasing attention. This paper first proposes a surface reconstruction algorithm based on curvature information, which is applicable to two different sensor structures: implanted FBG sensors and whisker array sensors. The design and analysis of these sensors are based on a pure bending model, where the corresponding bending curvature is obtained by measuring the wavelength shift of the fiber Bragg grating at the measurement points. Next, the paper elaborates on the surface reconstruction algorithm for the implanted FBG sensor. This sensor contains FBG sensing points that are evenly distributed. Curvature information corresponding to the position can be obtained based on the direction and magnitude of the wavelength shift. The fiber bending is considered as a connection of multiple arc segments, and the coordinates of the sensing points are calculated in the Cartesian coordinate system using the properties of the tangents. The fiber bending curve is then reconstructed by connecting the arc segments in MATLAB. Finally, the paper provides a detailed introduction to the surface reconstruction algorithm for the whisker array sensor. When the whiskers bend, the FBGs fixed on them act as curvature sensors. The curvature is determined by the FBG wavelength shift, and the three-dimensional coordinates of the whisker tip relative to the base are calculated based on a geometric model. MATLAB is then used to connect the whisker tip coordinates, completing the construction of the surface.

Towards smart and secure batteries: Linking pressure and temperature profiles with electrochemical behavior through hybrid optical fiber sensors

A hybrid sensing configuration combining fiber Bragg grating (FBG) with a Fabry-Perot interferometer is proposed for highly sensitive detection of pressure and temperature inside a commercial lithium-ion battery (LiB). The battery is also instrumented externally with FBGs to monitor its surface temperature variations. The LiB is operated under several cycling tests at different C-rates and environmental temperatures. High pressure and temperature resolutions of ±0.4 mbar and ±0.5 °C, respectively, are attained for the developed hybrid sensor, along with a minimum response time of 1.7 s. When the LiB is subjected to higher environmental temperatures, reduced thermal variations and higher pressure variations are registered by the optical sensor. Overall, during the cycling tests, the external temperature sensors closely follows the internal sensors behavior. Incremental capacity analysis derivative curves were systematically applied throughout the battery cycling experiments to unveil relevant insights into the interplay between pressure and temperature variations and the LiB electrochemical behavior. It was found that the pressure fluctuations present a “breathing profile” directly linked with the volume electrode lithiation and delithiation processes.

Chirped fiber Bragg gratings directly inscribed by a femtosecond laser in an ytterbium-doped fiber for spectrum recovery, loss compensation and effective use in a CPA scheme

Point-by-point femtosecond laser inscribed chirped Bragg gratings are good candidates for use in fiber chirped pulse amplification systems due to the high flexibility of their dispersion properties, low cost, and no length limitation. However, such gratings have two significant drawbacks: high losses and distortions of the short-wavelength part of the spectrum when operating in the normal group velocity dispersion mode. We propose a novel approach based on writing such gratings in a highly doped active fiber, which allows us to correct both shortcomings. We have also demonstrated, for the first time to our knowledge, a successful use of such gratings as stretchers in a fiber chirped pulse amplification system.

Ultrafast and Reproducible Fiber-Optic Hydrogen Sensor via a Tilted Fiber Grating With Pd/WO3 Nanocoating

Hydrogen, a high-density and clean energy, has been widely used in various critical applications. However, the safety risk caused by hydrogen leakage during storage and transportation is still a non-negligible issue. Therefore, it is necessary to offer hydrogen sensors with fast response and high repeatability, and it will be perfect for achieving in situ monitoring over the lifecycle of hydrogen production and utilization. Here, we propose a compact optical fiber sensor with a short section of the tilted Bragg fiber grating (TFBG) inscribed in the fiber core and a palladium and tungsten trioxide (Pd/WO3) combined film of 40 nm thickness over the fiber surface. The TFBG excites tens of narrow cladding resonances, part of which possess refractive indexes matching that of the Pd/WO3 coating and providing the high sensitivity to the surrounding hydrogen concentration change. The sensor offers improved sensing characteristics, including the fast response time (less than 10 s), high repeatability (over tens of measurement), and excellent linear response (higher than 99.6%) over the 0% to 3% concentration range.

Silicon photonics foundry fabricated, slow-light enhanced, low power thermal phase shifter

In this research, we developed a low-power silicon photonics foundry-fabricated slow-light thermal phase shifter (SLTPS) where the slow-light (SL) effect is achieved using an integrated Bragg grating (BG) waveguide. Heating the grating induces a red shift in the transmission spectrum, leading to an increased group index ng during operation, which facilitates a further reduction in the voltage needed for a π phase shift, i.e., Vπ. Additionally, we investigated a compact Mach–Zehnder Interferometer (MZI) that incorporates the SLTPS in both arms with a phase shifter length of 50 μm. A detailed theoretical analysis was conducted to address the non-idealities of the SL-MZI due to uneven optical power splitting and unbalanced loss in the two MZI arms. Vπ and power consumption for a π phase shift (Pπ) of the SL-MZI were quantified for operation in the slow-light regime, demonstrating a Vπ of 1.1 V and a Pπ of 3.63 mW at an operational wavelength near the photonic band edge. The figure of merit Pπ×τ is commonly used to assess the performance of thermal optical switches. The SL-MZI in this work has achieved a low Pπ×τ of 5.1 mW μs with an insertion loss of 4.4 dB, indicating a trade-off with the Vπ reduction.

Temperature and Lateral Pressure Sensing Using a Sagnac Sensor Based on Cascaded Tilted Grating and Polarization-Maintaining Fibers

This study introduces a Sagnac Interferometer (SI) fiber sensor that integrates Polarization-Maintaining Fibers (PMFs) with a Tilted Fiber Bragg Grating (TFBG) for the dual-parameter measurement of strain and lateral pressure. By incorporating a 6° TFBG with PMFs into the SI sensor, its sensitivity is significantly enhanced, enabling advanced multi-parameter sensing capabilities. The sensor demonstrates a temperature sensitivity of −1.413 nm/°C and a lateral pressure sensitivity of −4.264 dB/kPa, as validated by repeated experiments. The results exhibit excellent repeatability and high precision, underscoring the sensor’s potential for robust and accurate multi-parameter sensing applications.

A Novel FBG Placement Optimization Method for Tunnel Monitoring Based on WOA and Deep Q-Network

By employing the whale optimization algorithm’s (WOA) capability to reduce the probability of being stuck in a locally optimal solution, this study proposed an improved WOA-DQN algorithm based on the Deep Q-Network algorithm (DQN). Firstly, the mathematical model of Fiber Bragg Grating (FBG) sensor placement was established to calculate the reward of DQN. Secondly, the effectiveness and applicability of WOA-DQN were validated through experiments in nine cases. It indicated that the algorithm is far superior to other methods (Noisy DQN, Prioritized DQN, DQN, WOA), especially with the learning rate of 0.001, the initial noise 0.4, the hidden layer 3–512, and the updated frequency of 20. Finally, the FBG sensors were placed at [0°, 27°, 30°, 47°, 51°, 111°, 126°, 219°, 221°, 289°] to detect the accurate deformation of the tunnel with the maximum error 8.66 mm, which is better than the traditional placement. In conclusion, the algorithm provides a theoretical foundation for sensor placement and improves monitoring accuracy. It further shows great promise for deformation monitoring in tunnels.

Demodulating Optical Wireless Communication of FBG Sensing with Turbulence-Caused Noise by Stacked Denoising Autoencoders and the Deep Belief Network

Free-space optics communication (FSO) can be used as a transmission medium for fiber optic sensing signals to make fiber optic sensing easier to implement; however, interference with the sensing signals caused by the optical turbulence and scattering of airborne particles in the FSO path is a potential problem. This work aims to deep denoise sensed signals from fiber Bragg grating (FBG) sensors based on FSO link transmission using advanced denoising deep learning techniques, such as stacked denoising autoencoders (SDAE). Furthermore, it will demodulate the sensed wavelength of FBGs by applying the deep belief network (DBN) technique. This is the first time the real FBG sensing experiment has utilized the actual noise interference caused by the environmental turbulence from an FSO link rather than adding noise through numerical processing. Consequently, the spectrum of the FBG sensors is clearly modulated by the noise and the issue with peak power variation. This complicates the determination of the center wavelengths of multiple stacked FBG spectra, requiring the use of machine learning techniques to predict these wavelengths. The results indicate that SDAE is efficient in denoising from the FBG spectrum, and DBN is effective in demodulating the central wavelength of the overlapped FBG spectrum. Thus, it is beneficial to implement an FSO link-based FBG sensing system in adverse weather conditions or atmospheric turbulence.

Frozen and unfrozen moisture content estimation in coral calcareous sand during artificial freezing

In tropical areas where coral calcareous sands are prevalent, artificial freezing techniques are frequently employed during construction. However, the fundamental thermodynamic behaviors and moisture dynamics of calcareous sands under freezing conditions are poorly understood. Therefore, we conducted laboratory tests and developed a numerical model to capture the total moisture, liquid water, and ice contents of calcareous sand during artificial freezing. The thermal fiber Bragg grating (T − FBG) and frequency − domain reflectometry methods were used in the study. Freezing characteristic curves were quantitatively analyzed with taking into account the initial moisture content and ambient temperature. The results indicate that T − FBG effectively estimates the total moisture content in unfrozen and frozen calcareous sand, as well as ice content in frozen soil, with less than 0.029 m3/m3 error. Ice melting induced by T − FBG heating is affected by the initial moisture content, heating duration, power, and ambient temperature. However, the maximum change is below 0.008 m3/m3, which is negligible. The van Genuchten model accurately describes the liquid moisture–temperature relationship of unsaturated calcareous sand, with an R2 exceeding 0.98. The residual–initial moisture content relationship follows a quadratic function. During freezing, the temperature reduction aligns with the Kozlowski model, and the liquid moisture–temperature relationship follows a cubic polynomial function.

Shape sensing endoscope fiber

Minimally invasive and robotic surgeries are growing areas that benefit patients through reduced recovery time. Medical fiber optics play an important role in these procedures by enabling instrument navigation, imaging, sensing, power delivery, and diagnostics in a small form factor. One route to further miniaturization is to combine these functions, or a subset of these functions, into a single strand of optical fiber. In this work, we present a fiber and fan-in device that enables shape sensing, imaging, power delivery, and potentially additional sensing capabilities, such as temperature and/or pressure, in the same waveguide. The refractive index profile of the multimode waveguide in our fiber is similar to step index fibers used in laser delivery and is suitable for imaging applications; however, it also contains seven single mode cores twisted in a helix and with quasi-continuous Bragg gratings along their entire length, such as are used in fiber shape sensing. We first calibrate the transmission matrix of the multimode waveguide to enable the formation of a focused spot at the distal end of the fiber with a spatial light modulator. A second calibration allows us to reconstruct the shape of the fiber using optical frequency domain reflectometry in the twisted shape sensing cores. We show that these multiple functions can be performed simultaneously with our device and that changes in the curvature of the fiber correlate with the quality of the distal spot produced through the fiber, which is an important step towards maintaining the imaging calibration as the fiber is manipulated.

Broadband conversion between high-order angular modes based on double-sided exposure long-period fiber grating

Broadband high-order mode converters play a fundamental and crucial role in mode division multiplexing systems. Unfortunately, there have been no reports on achieving broadband mutual conversion between high-order modes using long-period fiber gratings (LPFGs). In this paper, based on the concept of “stepwise” progressive conversion (SPC), a double-sided exposure fabrication method of LPFGs to achieve broadband mutual conversion between high-order modes is proposed and demonstrated. Based on the proposed method, broadband mode conversion from LP11 to LP21, from LP21 to LP31 and from LP31 to LP41 with low insertion loss are achieved by utilizing low exposure power and shortened device lengths. The 10 dB bandwidths of the three converters are measured to be 80 nm, 110 nm, and 90 nm, respectively, and their insertion losses are all less than 0.2 dB. Theoretically, this method can achieve broadband conversion of even higher-order modes, providing a novel solution for the fabrication of stable broadband mode converters. More generally, such mode converters can convert between any two modes and are essential for building advanced MDM networks that require routing and mode switching.

Generation of High-Quality Cylindrical Vector Beams from All-Few-Mode Fiber Laser

Transverse mode control of laser intracavity oscillation is crucial for generating high-purity cylindrical vector beams (CVBs). We utilized the mode conversion and mode selection properties of two-mode long-period fiber gratings (TM-LPFGs) and two-mode fiber Bragg gratings (TM-FBGs) to achieve intracavity hybrid-mode oscillations of LP01 and LP11 from an all-few-mode fiber laser. A mode-locked pulse output with a repetition rate of 12.46 MHz and a signal-to-noise ratio of 53 dB was achieved with a semiconductor saturable absorber mirror (SESAM) for mode-locking, at a wavelength of 1550.32 nm. The 30 dB spectrum bandwidth of the mode-locked pulse was 0.13 nm. Furthermore, a high-purity CVB containing radially polarized and azimuthally polarized LP11 modes was generated. The purity of the obtained CVB was greater than 99%. The high-purity CVB pulses have great potential for applications in optical tweezers, high-speed mode-division multiplexing communication, and more.

Analysis and experiment of structural geometry for improved strain sensitivity of FBG sensors

AbstractThis paper presents analysis and experimental studies to significantly enhance the strain sensitivity of fiber Bragg grating (FBG) sensors by suitably modifying the host structure used for mounting the FBG. The proposed host structure is a novel, compact flexure beam-based design, specially engineered to amplify and convert horizontal strain into vertical strain more effectively. Its unique geometry includes circular sections for hinge connections, resulting in improved displacement amplification and reduced stress across the structure. Using ANSYS calculations and finite element analysis, simulations were conducted to evaluate the vertical deformation, stress, and longevity of the sensor's mechanical structure. Results from these simulations indicate an enhanced strain sensitivity of approximately 15.633 pm/με, a significant improvement over the 1.191 pm/με sensitivity observed with bare FBGs. Experimental tests were carried out on fabricated sensor structures to validate the enhancement in strain sensitivity. FBGs utilized in the experiments were inscribed using a 255 nm UV beam generated from a second harmonic copper vapour laser. The strain sensitivity of FBGs mounted on the optimized structure was found to increase up to 9.95 pm/με. The difference between simulation and experimental results are attributed to the partial absorption of strain by the adhesive used to affix FBGs.

Experimental and numerical investigations on the tensile response of pin-loaded carbon fibre reinforced polymer straps

Carbon fibre reinforced polymer (CFRP) pin-loaded looped straps are increasingly being used in a range of structural load-bearing applications, notably for bridge hanger cables in network arch rail and highway bridges. The static performance of such CFRP straps is investigated through experimental and numerical analyses. Finite element (FE) models based on both one-eighth and half pin-strap assembly geometries were modelled. The resulting strains, stresses, and applied loads were compared against experimental data obtained using Digital Image Correlation, Distributed Fibre Optic Sensing (DFOS), and Fibre Bragg Grating (FBG) Sensing. The FE models effectively captured local strain distributions around the vertex area, close to the pin ends of the straps, as well as in the mid-shaft region, and aligned reasonably with experimental observations. The half FE model accurately predicted the overall strain distribution when compared to DFOS data; however, higher strain magnitudes (by 0.45–10.2 %) and larger strain reductions were observed in some locations. Regarding failure loads, the FE models agreed well with Schürmann's analytical solution and the maximum stress criterion, exhibiting less than 2.5 % deviations from the experimental data. Furthermore, the predicted onset of strap failure (by delamination) in the half model agreed with experimental values, with a maximum variance of 9.2 %.

Research on gas pipeline leakage identification based on SE-2DCNN with ultra-weak fiber Bragg grating distributed acoustic sensing system

Abstract A new method for identifying gas pipeline leaks using an ultra-weak fiber Bragg grating (UWFBG) distributed acoustic sensing (DAS) system is proposed. To enhance the accuracy of gas leakage detection, an improved convolutional neural network (CNN) incorporating a two-dimensional structure based on the squeeze-and-excitation (SE) attention mechanism was introduced. The principle of acoustic leakage sensing using this technology is explained in detail, and an experimental setup simulating gas pipeline leaks is constructed. During this process, 9,340 DAS data points across varying leakage volumes and pipeline pressures were collected to create ten distinct datasets. The Mel-frequency cepstral coefficients (MFCC) are employed as the feature input for the optimized SE-2DCNN model, which performs identification tasks. The results show that this optimized model achieves an average leakage identification accuracy of 95.33%, demonstrating superior performance over other methods. This approach offers a robust reference for accurately detecting gas pipeline leakages.