Development of fast FBG interrogator with wavelength-swept laser

An efficient fiber Bragg grating (FBG) sensor integration system, which utilizes a small number of standard Telecom opto-electronics components, is presented in this paper. Wavelength-swept optical pulses were generated by driving a standard telecom DFB laser diode by high amplitude (>3 A) and short duration (300 ns) current pulses. A total laser diode's wavelength sweep in excess of 10 nm was achieved, which allows for simultaneous interrogation of several FBGs within similar wavelengths. The application of short duration wavelength-swept optical pulses also allows for time division multiplexing of small FBG arrays containing FBGs with overlapping characteristic wavelengths. When a short, wavelength-swept optical pulse is launched into the fiber containing single or multiple FBGs along its length, fractions of the launched pulse are back-reflected towards the detector. Since the launched pulse wavelength changes over the time, the reflections from the FBGs occur in the time moments that depend on the FBGs' characteristic wavelengths. Measurement of the time delay among back-reflected optical pulses is then used to determine the FBGs characteristic wavelengths. The experimental system demonstrated FBG wavelength readout resolution, which exceeded 3 pm at 1 KHz sampling rate, maximum sampling rate of over 40 KHz, and capability to readout/demultiplex over 30 FBGs located down a single optical fiber.

The authors propose and experimentally demonstrate a calibration process unit for mitigating the effects of nonlinearity and dependence on the ambient temperature for the fibre Fabry–Perot (FFP) filter. Additionally, the performance limits of the peak detection process unit based on the maximum detection algorithm according to the noise and the characteristics of the fibre Bragg grating (FBG) and FFP filter are presented. The experimental results obtained without and with the calibration process unit exhibited an average absolute error of <93.0 and 7.34 pm, respectively. The repeatability test results for the FBG interrogator showed an absolute error <2.19 pm. To investigate the performance limits of the peak detection process unit, the Bragg wavelength with variations in the noise of both the FBG reflection spectrum and the FFP filter transmission spectrum and with different characteristics of the FBG and the FFP filter were calculated. The calculated results for the given parameters show that the error of the mean value and the standard deviation increase with decreasing signal‐to‐noise ratios of both the FBG and FFP filter. Additionally, it was confirmed that the errors increase with the increase of the full‐widths at half‐maximum of both the FFP filter and the FBG and with the decrease of the Bragg wavelength intervals.

The real-time monitoring technologies of smart civil structure using fiber Bragg grating (FBG), including the wavelength demodulation technology of FBG, are researched extensively at home and abroad. To improve the accuracy of demodulation system of FBG sensors, based on a fiber comb filter, a wavelength-demodulation method of FBG was proposed and an experiment platform was designed to demodulate the FBG wavelength for smart civil structure. The reinforced concrete embedded fiber Bragg gratings became the intelligent civil structure on which the experiment of structural health monitoring was done. Experimental results show that, based on a fiber comb filter, the FBG wavelength demodulation method can be used to demodulate the FBG wavelength with high speed and high precision, which can be used extensively in large-scale multipoint monitor engineering. During the experiment, the fiber Bragg gratings embedded in reinforced concrete show good sensing properties, and can respond rapidly to strain with a stable performance.

This paper introduces ensemble deep learning (EDL) models for accurate demodulation of Fiber Bragg Grating (FBG) sensor spectra, with input training data enhanced through the numerical square method (NSM) technique. The technique combines numerical squaring with an EDL to improve prediction accuracy in noisy and overlapping spectral conditions. The proposed system uses an FBG interrogator with sensors embedded in transparent liquid containers to detect liquid level changes via Bragg wavelength shifts. However, changes in the liquid level shift the float position, causing overlap or cross-talk between adjacent sensors. To address this, the NSM enhances signal clarity by boosting authentic FBG responses and minimizing noise. Single, double, and triple NSM operations are applied to the experimental data to sharpen the reflection peaks and enhance overall signal quality, ensuring the data are well-prepared for training the EDL model. The EDL model combines CNNs for spectral feature extraction and LSTMs and GRUs for sequential pattern recognition and efficient learning, effectively capturing both spectral and sequential features. The EDL model is trained on the dataset enhanced by the NSM technique and validated using unseen experimental data to evaluate its performance. The results confirm that NSM efficiently sharpens reflection peaks, improves signal clarity, and reduces noise in FBG spectra, while the EDL model effectively demodulates the overlapping spectra. Experimental results demonstrate that the integrated NSM-EDL approach outperforms traditional machine learning and standalone deep learning models in terms of prediction accuracy, minimal errors, and computational time. The proposed method is cost-effective, hardware-efficient, and ideal for real-time multiplexed FBG sensing applications, such as liquid level monitoring.

Extraction and processing of real time strain of embedded FBG sensors using a fixed filter FBG circuit and an artificial neural network

We present a fiber Bragg grating (FBG) interrogation method using a micro-controller board and optical filter that achieves high strain sensitivity and high dynamic range. This interrogation method allows high sensitivity detection of ultrasonic waves superimposed on low-frequency (on the order of 100Hz) vibrations of arbitrary magnitude. One possible application is <i>in-situ</i> structural health monitoring of windmill blades exposed to strong winds by using FBG sensors for detection of ultrasonic waves. Interrogator operation is based on the edge filtering method using a broadband source, fiber Fabry-Perot filter and a micro-controller board which acts as a control feedback loop that locks the filter wavelength to the mid-reflection point on the FBG spectrum. Wavelength locking method allows high sensitivity for edge filtering of high-frequency waves, while the feedback signal is the measurement of low-frequency vibration with high dynamic range. The concept of the interrogator operation and different implementations are described and discussed with experimental results.

High-speed fiber Bragg grating (FBG) interrogation based on arrayed waveguide gratings (AWGs) enables parallel, scan-free interrogation but is fundamentally limited by interrogation discontinuities when the FBG spectrum traverses adjacent AWG channels. This issue originates from insufficient spectral overlap at channel boundaries and leads to wavelength jumps during large or rapid spectral excursions. We report a compact AWG-based FBG interrogator that overcomes this limitation through a hardware-software co-design strategy. Contrary to conventional AWG designs that prioritize low crosstalk for optical communications, we deliberately utilize a high-crosstalk AWG to introduce substantial inter-channel spectral overlap, thereby ensuring a smooth and monotonic ratiometric response across channel boundaries. To further eliminate residual numerical discontinuities, a real-time wavelength jump suppression algorithm (WJSA) is developed to detect channel-switching events and apply adaptive reference-wavelength correction. Experimental results demonstrate a high interrogation linearity (R2=0.9992), even for narrowband FBGs with a bandwidth of 0.20 nm. The interrogator supports a sampling rate of up to 500 kS/s, enabling accurate dynamic strain measurements up to 50 kHz and resolving transient impact responses with microsecond-level temporal resolution. The proposed approach addresses a key limitation in AWG-based FBG interrogation and provides a scalable and cost-effective solution for high-speed structural health monitoring.

A highly integrated optical fibre sensor for simultaneous discrete dynamic strain and distributed static strain/temperature measurements is experimentally demonstrated by combining Brillouin optical time domain analysis and time-division-multiplexed fibre Bragg grating (FBG) interrogation. A highly integrated sensor system is demonstrated by using a single laser source, one shared receiver block and broadband, low reflectivity FBGs.

An interrogation scheme based on wavelength-to-time mapping to achieve ultrafast, high-precision, and large dynamic range interrogation of fiber Bragg grating (FBG) sensors is proposed and experimentally demonstrated. The wavelength-to-time mapping, also called temporal self-imaging effect, is realized in the optical domain, using a dispersive element that has a large group velocity dispersion. For a practical dispersive element, higher order dispersions exist, which makes the wavelength-to-time mapping nonlinear. Thus, an interrogation system based on wavelength-to-time mapping without considering the high-order dispersion would reduce the interrogation accuracy. In this paper, for the first time to the best of our knowledge, a mathematical model that incorporates higher order dispersion to achieve an accurate wavelength-to-time mapping is developed, which is then verified by a numerical simulation. An FBG-based strain sensor interrogated based on the developed wavelength-to-time mapping scheme is experimentally investigated. The system has a sampling speed of 48.6 MHz, a dynamic range as large as 20 nm, and a sensing accuracy as high as 0.87 ?? for a single-shot measurement.

We demonstrated a MHz speed wavelength-swept fiber laser based on the active mode locking (AML) technique and applied to interrogation system of an array of fiber Bragg grating (FBG) sensors. MHz speed wavelength sweeping of wavelength-swept fiber laser can be obtained by programmable frequency modulation of the semiconductor optical amplifier (SOA) without any wavelength tunable filter. Both static and dynamic strain measurement of FBG sensors were successfully characterized with high linearity of an R-square value of 0.9999 at sweeping speed of 50 kHz.

Wavelength-swept laser is one of the most critical common components of fiber Bragg grating (FBG) sensors. However, a fast, stable, integrated and low-cost multi-channel wavelength-swept laser array is still unavailable. In this article, a multi-channel simultaneous wavelength-swept DFB laser array based on the reconstruction-equivalent-chirp (REC) technique is proposed and manufactured. The REC technology simplifies the fabrication process and greatly reduces the cost of the laser. The laser array contains 4 lasers in parallel with integrated heating resistance for thermal tuning to broaden the wavelength-tuning range. Each single-wavelength DFB laser introduces a π-phase shift structure, which is used to improve the single-mode performance of the laser. Meanwhile, the active multiplexer responsible for coupling and an optical amplifier (SOA) responsible for compensating the coupling loss of the laser are also integrated on the same chip. The driving circuits of the laser use FPGA to control the DAC chip to obtain precise current output and realizes continuous linear output of wavelength by changing the injection current size. The packaged laser module can realize a continuous wavelength-swept range of 2.4 nm per channel with the SMSR over 40 dB, achieving a simultaneous sweep of four channels with good scanning linearity and scanning speed. The work of this paper realizes the integration of linear wavelength-swept light sources, which creates the conditions for a low-cost, small-volume multi-channel sensing system in the future.

The continuous Non-Destructive Evaluation of assets for long-term assurance of performance has led to several developments over the deployment of a Real-Time Structural Health Monitoring (SHM) system. Considering the challenges involved under the implementation of an SHM system for the applications working under harsh environmental conditions with limited access to power sources this work is aimed to contribute towards overcoming those challenges by using the noise from the structure’s machinery or any ambient source as an alternative energy source and employing Fiber Optics based sensing, for its applicability under harsh environments. The required SHM system is realized with the cross-correlation of a fully diffused noise field, sensed using the Fiber Bragg Grating (FBG) sensors at two random locations. With no control on the input received as noise, to this end, a method is developed based on a Deep Learning framework, which is aimed towards a Universal Deployment of the passive SHM system. The methodology is designed to perform the health monitoring of the system, independent of the input perturbations. The validation performed on simulation data has demonstrated the feasibility of the developed technique towards the required kind of passive SHM system.

We demonstrate diagnosis of several machine-condition failures using wide-frequency-band interrogation of fiber Bragg grating (FBG) sensors. In collaboration with Israel's national water company Mekorot Ltd., a scaled-down version of a semi-submerged pumping system was constructed. By monitoring broadband signals from DC to ultrasound (>M H z), at different points of the engine and the submersed pump, the system was able to diagnose incipient cavitation, faulty bearings, and submerged dynamic water-level measurements. In addition, a metal embedded FBG sensor was investigated, revealing the potential of using FBGs in applications where bonding is problematic such as bearing housing. These results prove that wideband data acquisition, together with advanced analytics, could open a variety of new applications in the fields of structural health and machine-condition monitoring.

Optical frequency combs (OFC) generated by electro-optic modulation of continuous-wave lasers provide broadband coherent sources with high power per line and independent control of line spacing and the number of lines. In addition to their application in spectroscopy, they offer flexible and optimized sources for the interrogation of other sensors based on wavelength change or wavelength filtering, such as fiber Bragg grating (FBG) sensors. In this paper, a dual-OFC FBG interrogation system based on a single laser and two optical-phase modulators is presented. This architecture allows for the configuration of multimode optical source parameters such as the number of modes and their position within the reflected spectrum of the FBG. A direct read-out is obtained by mapping the optical spectrum onto the radio-frequency spectrum output of the dual-comb. This interrogation scheme is proposed for measuring fast phenomena such as vibrations and ultrasounds. Results are presented for dual-comb operation under optimized control. The optical modes are mapped onto detectable tones that are multiples of 0.5 MHz around a center radiofrequency tone (40 MHz). Measurements of ultrasounds (40 kHz and 120 kHz) are demonstrated with this sensing system. Ultrasounds induce dynamic strain onto the fiber, which generates changes in the reflected Bragg wavelength and, hence, modulates the amplitude of the OFC modes within the reflected spectrum. The amplitude modulation of two counterphase tones is detected to obtain a differential measurement proportional to the ultrasound signal.

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.