Fiber Bragg Grating Wavelength Research Articles

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.

Estimation of Li-ion battery SOH based on factors combination of FBG wavelength shift and charge-discharge process

For the purpose of daily battery maintenance, safety forecasting, and energy ladder use, it is crucial to accurately estimate the state of health (SOH) of Li-ion batteries. The external fiber Bragg grating (FBG) sensor is used in this work to collect the signal fluctuations of the wavelength shift in different areas during the Li-ion battery's charge-discharge cycle using a combination of feature analysis and data-driven method, and the characteristics of the wavelength shift and the charge- discharge process in different regions under 125 cycles are statistically analyzed. The reaction degree of Li-ion battery in different areas was compared by wavelength shift value. The wavelength shift factor and charge-discharge process factor related to battery SOH were extracted and trained in the NGO-BP regression model. The experimental results show that the combination of fiber Bragg grating wavelength shift factor and charge-discharge process factor can accurately estimate the SOH of Li-ion battery, and the prediction effect of three areas combination is the best, the goodness of fit R2 is 0.99958, the mean square error MSE is 2.71 × 10−4, the mean absolute error MAE is 1.3373 × 10−2, the root mean square error RMSE is 1.6462 × 10−2, and the mean absolute percentage error MAPE is 1.3679 × 10−2%.The combination of negative electrode and middle area uses fewer sensors to obtain higher prediction accuracy, and its cost performance is the highest. The utilization of fiber Bragg grating wavelength shift factor and charge-discharge process factor has essentially led to the accurate calculation of Li-ion battery SOH, which holds significance for battery health monitoring as well as the design and development of battery management systems.

Tac-scope: An endoscope integrated with soft sensor for real-time tactile feedback

In order to improve the safety of endoscopic surgery, a flexible endoscope with real-time tactile feedback (Tac-scope) has been proposed. It integrates a soft sensor at the end embedded with fiber Bragg grating (FBG) to detect the contact force with the lumen wall, while retaining the original function of the endoscope. In this article, theoretical analysis, simulated analysis, and experiments have been implemented, obtaining the mapping from FBG wavelength shifts to the force magnitude and orientation. To verify the real-time detection and feedback capability, tests are conducted on the bronchial model. The results show an average reduction of 60% in contact force and 30% in operation time. The linearity of Tac-scope force detection is 0.991, the repeatability error is 6.46%, the resolution is 8.8 mN, the sensitivity is 0.693 nm/N, the average error is 4.4%, and the error of orientation detection is 3.57%. Such merits indicate that the proposed Tac-scope has huge potential in endoscopic surgeries.

On-line cure monitoring of phenol formaldehyde resin using embedded fiber Bragg grating sensor

On-line cure monitoring techniques have shown advantages for identifying the stages of curing and can lead to smart curing process of resin system and its composites. In this study, an on-line measuring technique with fiber Bragg grating (FBG) sensors was used to gain clear understanding of the curing stages of phenolic resin, as well as to determine its chemical shrinkage level. The FBG sensors were embedded in phenolic resin and worked under temperature raising and isothermal conditions. Through the interface between FBG sensor and resin, curing shrinkage strain was transferred to the grating, changing the central wavelength of FBG and producing strain. The feasibility of FBG sensors for monitoring chemical shrinkage during curing was verified by employing epoxy and benzoxazine resins that exhibits low chemical shrinkage. For cure monitoring of phenolic resin, the results show that the strain signal can be corresponded to various responses, such as solvent volatilization, hydroxylation and dehydration condensation reactions during temperature raising curing process. Through these strain characteristics, the curing state of phenolic resin can be obtained, which degree of cure ranges from 0.05 to 0.9. In isothermal curing process of phenolic resin, an exponential correlation between chemical shrinkage induced compressive strain and degree of cure of resin was identified, indicating that the real-time compressive strain is proportional to the degree of cure of phenolic resin. By evaluating real-time curing shrinkage levels, the estimation of curing degree of phenolic resin can be achieved utilizing exponential correlation of curing degree and curing shrinkage level.

Highly precise FBG wavelength demodulation method with strong multiplexing ability and positioning function based on time-domain detection.

Based on the theory of the microwave photonic filter (MPF), to our knowledge, a novel fiber Bragg grating (FBG) wavelength demodulation method based on time-domain detection is proposed. The method uses VNA (vector network analyzer) to measure the S21 parameter of the sensor system, and converts them to the time-domain through inverse discrete Fourier transform (IDFT), The wavelength demodulation and positioning of FBG can be realized by measuring the amplitude and position of the time-domain peak. In order to improve the number of FBG multiplexes, a method is proposed to eliminate the effect of spectrum overlap by normalization in the case of two FBGs and three FBGs. The experimental results show that the temperature sensitivity is 0.00503 RAC/°C, the positioning resolution of the system is 1.25 cm, and the limit of the wavelength difference between two FBGs allowed by the system is 0.25 nm. This method has the advantages of high demodulation precision, strong multiplexing ability and high precision positioning, and has broad application prospects.

Numerical Investigation of Stress-Strain State Effects on Strain Measurements with Fiber Bragg Grating Sensors

This study investigates the behaviour of resonant wavelengths of Fiber Bragg Gratings (FBG) inscribed within optically isotropic fibers under transverse loading, both in free and embedded conditions. A numerical-analytical approach is employed, utilizing the finite element method to calculate strain tensor components in the optical fiber core, followed by an analytical determination of resonant wavelengths and reflected FBG spectrum shape. The research demonstrates the influence of the ratio of host material and optical fiber elastic moduli on the birefringence level in FBG area under transversal loading. Based on analytical model of FBG spectrum simulation the discrepancy between analytically calculated and experimentally recorded resonant wavelength shifts in FBG embedded within isotropic material under varying transverse load levels is demonstrated.

Application of a fiber Bragg grating temperature sensing method based on support vector regression optimized by a genetic algorithm for the decreasing external ambient temperature case.

We studied the application of the fiber Bragg grating (FBG) temperature sensing method based on support vector regression optimized by a genetic algorithm (GA-SVR) for constant and decreasing external ambient temperature cases by simulation. The external ambient temperature could be retrieved from both the transient FBG wavelength and its corresponding change rate using GA-SVR, before the FBG temperature sensor reached the thermal equilibrium state with the external ambient temperature. FBG wavelengths and their corresponding change rates in the cases of FBG sensor temperatures higher and lower than the external ambient temperature were studied and used to construct the training data set. We found that there exist singularity points in the curves of the wavelength change rate when the FBG sensor temperature is higher than the external ambient temperature in some cases, which is different from the case where the FBG sensor temperature is lower than the external ambient temperature. Its application for sensing the constant and decreasing external ambient temperature in real time was demonstrated with an accuracy of 0.32°C in those two cases. It also indicates that for real applications of this temperature sensing method where the external ambient temperature varies randomly, the FBG sensor temperature changes rather than the external ambient temperature changes play the dominant role. What is more, the demodulation time was decreased to 0.002s, which is approximately 0.05‱ of the time constant of the FBG temperature sensor. In other words, this method makes it possible to realize the external ambient temperature determination using a time smaller than the time constant of the FBG sensor. The high sensing accuracy and fast demodulation speed are crucial for future high-performance real-time FBG temperature sensing.

A novel fast response and high precision water temperature sensor based on Fiber Bragg Grating

A novel fast response and high precision water temperature sensor scheme based on gallium alloy sensitivity enhanced Fiber Bragg Grating(FBG) is proposed and experimentally demonstrated. In order to achieve faster temperature response speed of the sensor, a fiber Bragg grating is encapsulated in a single-end sealed metal tube which is filled with liquid gallium alloy. The very high thermal conductivity of the liquid gallium alloy that is filled in the metal tube gives rise to an experimental sensitivity of 30 pm/℃. Thanks to accurate and optimal design of metal tube structure parameters, the sensor exhibits an excellent response speed of 43 ms/℃ in water. Very good linearity between center wavelength of FBG and temperature is also achieved in the experiment. The research result of this paper is especially useful for applications where rapid temperature response and high precision are required at the same time, such as ocean CTD(Conductivity Temperature Depth) measuring equipment, ocean hydrology and underwater submersible.

SOI-based 12 × 12 arrayed waveguide grating for fiber Bragg grating interrogation system

Fiber Bragg grating (FBG) interrogator is a scientific instrument that can indirectly monitor physical quantities such as temperature and pressure by detecting the center wavelength of FBG. The arrayed waveguide grating (AWG), one of the fundamental parts of the FBG interrogation system, is essential for driving the downsizing of the system and high-speed rate. In this paper, a 12-channel silicon on insulator based AWG with an average 3 dB bandwidth of 2.23 , insertion loss of less than 5 dB, and crosstalk of −16.64 dB is designed and fabricated for a photonic integrated FBG interrogation system. The wavelength resolution of the FBG interrogation system of this AWG is 8 , and the wavelength accuracy measured in the dynamic range of 0.8 is 10.59 . This AWG can be well used in FBG interrogation systems.

Continuous Fiber Bragg Grating Optical Sensors for Superconducting Magnet Quench Detection: The Effects of Attenuation and Position in the Array

Quasi-continuous arrays of fiber Bragg gratings (FBGs) show great promise for quench protection in superconductors. The number of identical gratings and the reflectivity of the individual gratings are important parameters determining the sensitivity of the system to a local temperature or strain perturbation. We apply strain to shift the Bragg wavelength of a single FBG through the spectrum of an array of up to 1000 identical gratings, and map out the detection sensitivity for a given <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Delta \lambda$</tex-math></inline-formula> relative to the peak reflectance of the FBG array, and show that the position of the perturbed FBG matters only due to the broadband attenuation of the probe light down the array. Varying the number of gratings in the array shows the interplay between the number of gratings, the reflectivity of the gratings, and the sensitivity of the system. We demonstrate that the ability to model the spectrum of the FBG array is crucial to predicting system performance.

Tunable Random Fiber Laser Based on Dual-Grating Structure

In order to reduce the pumping threshold and achieve a short-cavity single-mode transmission with a narrow-linewidth random fiber laser, we propose a tunable random fiber laser based on the combination of random grating and highly reflective fiber Bragg grating (FBG). Theoretical modeling of a random refractive index-modulated fiber grating was carried out. Random grating is regarded as a linear combination of uniform fiber gratings with different periods. Simulation calculations were performed using the transfer matrix method to determine the preparation parameters. Under the premise of satisfying light localization, a point-by-point method was used to write a random grating in a single-mode fiber using a femtosecond laser according to the simulated parameters. We constructed a random fiber laser with a linewidth of 1.68 kHz and a threshold of 29.2 mW using a random grating and a highly reflective FBG combined with an erbium-doped fiber. Due to the broad scattered wavelength range of the random grating, by changing the central wavelength of the high-reflection FBG, the tunable wavelength of the output laser was realized, and the tunable range was 0.847 nm (1549.110–1549.957 nm). Moreover, the laser’s central wavelength and output power are stable for a long time. Compared with other lasers, the proposed laser has the advantages of a lower threshold, shorter cavity length, narrower linewidth, and a relatively simple structure.

Detection of peak wavelength of multi-FBG using higher-order derivative of wavelets multiresolution analysis and maximum likelihood estimation

The peak wavelength of fiber Bragg grating (FBG) using the higher-order derivative of Wavelets multiresolution analysis and maximum likelihood estimation is proposed. The FBG reflected spectrum is decomposed at the different level using wavelet multiresolution analysis and the higher-order derivative is applied. The first-order derivative is applied to the calculated desired decomposed level to find the zero-crossing point. The 2nd order derivative is applied and the extrema at the corresponding zero-crossing points are calculated. Further, the proceeding derivative, the 4th order derivative is applied and sharper maxima corresponding zero-crossing point is calculated. The maximum likelihood estimation-based statically method is applied to predict the exact peak wavelengths with good efficiency and low error. The proposed peak detection algorithm is also used in the partially overlapped with weak and non-uniform peaks of cascaded FBGs.

Optical fiber flow sensor based on a lever-hinge configuration.

Based on a lever-hinge structure, a target-type fiber Bragg grating (FBG) flow sensor is proposed. Differential measurements of temperature and pressure are achieved using two FBGs. The design idea of the sensor is demonstrated from both theoretical and experimental aspects, and the relationship between FBG wavelength and temperature and the relationship between FBG wavelength and volume flow rate were established, respectively. The sensor is compact with good resolution, high stability, wide measurement range, and easy fabrication, and can be applied to measure temperature and volume flow rate in injection wells.

Experimental Demonstration of Peak Wavelength Measurement of Multiplexing Fiber Bragg Gratings Using Convolutional Neural Network

We propose a peak detection method for measuring fiber Bragg gratings (FBGs) using convolutional neural network (CNN) to improve the performances of wavelength division multiplexing. In wavelength division multiplexing, each FBG occupies a certain wavelength range; therefore, the number of FBGs that can be installed is limited by the wavelength band of the light source. To address this issue, methods for overlapping multiple FBGs of the same wavelength within a single occupied wavelength range have been studied. This contributes to improving the limit of multipoint FBGs manifold. However, this method results in the complex overlapping of multiple FBG reflectance spectra making it difficult to accurately measure the peak wavelengths of individual FBGs using conventional peak detection methods. Therefore, we developed a peak detection process using CNN, which is suitable for identifying unique feature data. Each FBG of the same wavelength was characterized to have a unique spectral shape by assigning a different full width at half maximum to each. We introduced noise-additive learning, a well-known method of data augmentation that increases tolerance to variations in the experimental signal. As a result, the standard deviation for peak wavelength detection significantly improved to 2.8 pm and the strain measurements with three complex overlapping FBGs were successfully demonstrated. The CNN model is the first to solve the problem of three overlapping FBGs for arbitrary wavelength changes. Furthermore, the developed peak detection process was found to be applicable to measurements that combined multiplexing of FBGs of either identical or different wavelengths.

Ultra-high-temperature sensing using fiber grating sensor and demodulation method based on support vector regression optimized by a genetic algorithm.

We propose an ultra-high-temperature sensing method using a fiber Bragg grating (FBG) and demodulation technique based on support vector regression optimized by a genetic algorithm (GA-SVR). A type-I FBG inscribed by a femtosecond laser in a silica fiber was packaged with a tube and used as a temperature sensor. The external ambient temperature was retrieved from the transient FBG wavelength and its increase rate in reaching thermal equilibrium of the FBG with the external environment using GA-SVR. The temperature sensing in the range of 400 to 1000 °C was realized with an accuracy of 4.8 °C. The highest sensing temperature exceeded the FBG resisting temperature of 700 °C. The demodulation time was decreased to approximately 15 s, only 3.14% of the FBG sensor time constant. The proposed method could realize the external ambient temperature determination before the FBG temperature reached the thermal equilibrium state, which enables to attain a demodulation time shorter than the time constant of the FBG sensor and a sensing temperature higher than the FBG resisting temperature. This method could be potentially applied in temperature inspection of combustion and other fields.

Laser-Based Optical Wireless Communications for Internet of Things (IoT) Application

Internet of Things (IoT) is enabled by the integration of communication and sensor systems that are used to collect important information from objects around the world. In this article, we proposed the integration of laser-based optical wireless communication (OWC) with a fiber sensor system for IoT applications. OWC can be utilized in a harsh environment to send and receive communication and sensor signals in a wireless means. Moreover, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. As compared to mechanical and electrical sensors, optical fiber sensors have numerous benefits, including the tolerance to electromagnetic interference (EMI), small size, lightweight, high bandwidth, low cost, provide distributed sensing, high sensitivity, and electronic devices are not required at the sensor point. Moreover, we proposed a deep variational autoencoder (DVAE) model to estimate the strain changes and peak wavelength of multiple fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment. The result showed that our proposed DVAE model can estimate the strain changes and peak wavelength of FBGs with low root mean squared error (RMSE) and high estimation accuracy. Furthermore, the performance of the proposed integration of OWC with the fiber sensor system achieves a clear eye diagram and excellent bit error rate (BER) curve.

FBG array based wavelength calibration scheme for Fourier domain mode-locked laser with pm resolution and hourly stability.

We demonstrate a fiber Bragg grating (FBG) array based wavelength calibration scheme for Fourier domain mode-locked (FDML) laser. The wavelength interval and the temperature feedback module of the FBG array are designed to ensure the reference stability of the wavelength calibration scheme. Combined with the calibration scheme, the FDML laser with a tunable wavelength range of ∼60 nm, a center wavelength of 1300 nm and a sweep frequency of 39.63 kHz is built up to demonstrate its feasibility. The FBG wavelength demodulation based on the calibrated FDML laser system shows a wavelength resolution of 2.76 pm and hourly stability of 10.22 pm.

Self-healing integration of fiber/FSO communication and sensor network for improving survivability

In this paper, we proposed a novel self-healing fiber/free-space optics (FSO) communication integrated with a sensor network for simultaneous transmission of optical communication signal and sensing signal as well as a function of fault protection by using a coarse wavelength-division multiplexer (CWDM). The combination of CWDM and fiber integrated with FSO transmission channel is incorporated to design a cost-effective, flexible network and increase the coverage of transmission distance. The experiment result proves that the fiber integrated with an FSO transmission channel achieves a clear constellation diagram and best error vector magnitude (EVM) value. On the other hand, the scanning-laser interrogation system is used for data acquisition in the strain-based fiber Bragg grating (FBG) sensor system. Moreover, the radial basis function neural network (RBFNN) algorithm is used to estimate the central wavelength of FBGs.

High-Speed and High-Resolution Optical Fiber Sensor Interrogation Based on Optical Injection in Semiconductor Laser and Microwave Filtering

Real-time and high-speed interrogation of optical fiber sensors normally requires sophisticated detection systems. Here a novel microwave photonic approach for interrogation of high-speed and high-resolution optical fiber sensors based on optical injection in a semiconductor laser and simple passive microwave frequency filtering is proposed and experimentally demonstrated. An intensity-modulated master laser is injected into a semiconductor laser to produce a wavelength scanning optical sideband. A fiber Bragg grating (FBG) sensor is embedded into a fiber ring laser. Beating of the scanning optical sideband and the fiber ring laser wavelength at a photodetector generates a linearly frequency-chirped microwave signal. The real-time wavelength shift of the FBG sensor is converted into the change of the microwave center frequency. After a simple passive microwave bandpass filter, two electrical pulses are obtained corresponding to positive and negative frequency sweeping. The FBG wavelength can be retrieved from the time interval of the two pulses. A proof-of-concept experiment to measure an FBG strain sensor has been carried out. A high interrogation speed of 1 MHz and measurement sensitivity of 17.3 ns/μϵ have been achieved.

Real-Time Battery Temperature Monitoring Using FBG Sensors: A Data-Driven Calibration Method

Battery storage has an important role to play in integrating large-scale renewable power generations and in transport decarbonization. Real-time monitoring of battery temperature profiles is indispensable for battery safety management. Due to the advantages of small size, resistance to corrosion, immunity to electromagnetic interference, and multiplexing, fiber Bragg-grating (FBG) sensing has received substantial interest in recent years for battery temperature measurement. However, traditional temperature calibration for FBG sensors often requires a high-standard reference and causes the sensors to fail to be consistent during the calibration or recalibration processes. To tackle the challenges, an ensemble data-driven calibration method is developed in this article for FBG sensors. The calibration model consists of a linear part and a nonlinear part. First, the fuzzy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${C}$ </tex-math></inline-formula> -means (FCM) algorithm is used to extract the linear relationship between the measured FBG wavelength shift and temperature variation. Then, the empirical mode decomposition (EMD) technique is used to classify the intrinsic mode functions (IMFs) and the remainder of the unmodeled nonlinear information. The unmodeled nonlinear information is further compensated using battery state of charge (SOC) and cycle number information. The experimental results confirm that the proposed temperature calibration method achieves desirable accuracy and reliability, with both the mean absolute error (MAE) and root mean square error (RMSE) being around 0.2 °C, respectively. Compared with the traditional temperature calibration method, the proposed approach can be used online in real-life applications.