Hybrid optical fibre sensor for simultaneous dynamic FBG interrogation and distributed static strain/temperature measurements

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 objective of this research is the construction of a structural health monitoring system that uses fiber Bragg grating (FBG) to determine the health of structures. We develop fast FBG interrogator for real-time measurement of the reflected wavelength of a multipoint FBG to monitor the broadband vibration of a structure. This FBG interrogator, which combines a wavelength-swept laser and a real-time measurement system is capable of measuring wavelength within a standard deviation of 2×10 -3 nm or less. We have demonstrated that the FBG interrogator is able to measure vibration that has a resonance frequency of 440 Hz at intervals of 0.1 ms with a multipoint FBG.

Distributed fiber sensing (DFS) can provide real-time signals and warnings. The entire length of fiber optic cable can act as a sensing element, but the accuracy is sometimes limited. On the other hand, point-to-point fiber sensing (PPFS) is usually implemented using one or more fiber Bragg gratings (FBGs) at specific positions along with the fiber for the monitoring of specific parameters (temperature, strain, pressure, and so on). However, the cost becomes expensive when the number of FBGs increases. A hybrid fiber sensing scheme is thus proposed, combining the advantages of DFS and PPFS. It is based on a Brillouin optical time-domain analysis (BOTDA) fiber system with additional FBGs embedded at certain positions where it is necessary to detect specific parameters. The hybrid fiber sensing system has the advantages of full sensing coverage at essential locations that need to be carefully monitored. In our work, the test results showed that the proposed system could achieve a sensing distance of 16 km with the single-mode fiber with a 2 m spatial resolution. For FBG parameter measurements, the temperature variation was 52 °C, from 25 °C to 77 °C, with a temperature sensitivity of 23 pm/°C, and the strain was from 0 to 400 µε, with a strain sensitivity of 0.975 pm/µε, respectively, using two FBGs.

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.

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 planar lightwave circuit-based multi-channel arrayed waveguide grating (AWG) is used as a critical part of the fiber Bragg grating (FBG) interrogation unit and designed to be integrated into the fiber grating sensing system. We designed and fabricated a high-performance, 40 channels AWG in the device, enabling whole C-band wavelength demodulation while maintaining high-measurement resolution. The AWG was designed to have 100-GHz channel spacing; the channel crosstalk was measured to be −45 dB. An AWG-based FBG interrogation system was built to analyze the characteristics of our unit. The testing result shows that our system has the capability of demodulating wavelength from 1526.438 to 1563.863 nm with wavelength accuracy within ±10 pm; the wavelength resolution is measured to be 1 pm. Our testing result confirms that an AWG-based FBG interrogator is an excellent choice for FBG sensing systems.

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.

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.

In recent years, many conventional image denoising techniques have been intensively studied to enhance the signal to noise ratio (SNR) of Brillouin optical time domain analyzer (BOTDA), due to their superior denoising performance to one-dimensional methods. However, in the case of low sampling rate, the details of the signal are smoothed out due to less useful information, resulting in a degradation of the spatial resolution. Moreover, these conventional denoising algorithms are quite time-consuming compared with the BOTDA measuring time. To overcome these drawbacks, we employ a feed-forward convolutional neural networks (CNN) based image denoising for BOTDA. A conventional BOTDA system with 15 ns pulse width is implemented to demonstrate the effectiveness of the exploited CNN-based denoising method. The actual electrical noise signals of the BOTDA at different sampling rates are collected to synthesize training samples. The CNN model is trained with the noise and simulated BOTDA signals. Experimental results show that SNR improvement of 13.43 dB, 13.57 dB, and 12.9 dB is achieved at a sampling rate of 500 MSa/s, 250 MSa/s, and 125 MSa/s, respectively, via the trained CNN denoiser. No spatial resolution distortion can be observed in the denoised BOTDA signals. Besides, the CNN denoiser only takes 0.045 s to process a 151 × 50000 image benefiting from GPU computing. This processing time is negligible compared with the acquisition time of BOTDA, which makes real-time denoising possible.

A review of previous studies on the applications of optical fiber sensors in geotechnical health monitoring

In this paper, we summarize our recent research work on two types of optical fiber sensors: long distance sensor and biomedical sensor. For long distance sensing, we demonstrated our 150-km long distance fiber Bragg Grating (FBG) temperature and vibration sensor system and Brillouin optical time domain analysis distributed sensor system. For biomedical sensing, we demonstrated our microbend fiber sensors for measurements of breathing rate/heat rate and Ballistocardiogram waveform. A new sensor for patient's breathing measurement by using fiber loop ringdown spectroscopy is also introduced.

Low thermal sensitivity and cross sensitivity of Fiber Bragg Grating (FBG) towards the applied strain, temperature make FBG implementation complicated in composite materials at cryogenic conditions. In order to alleviate this problem, our work focuses on simultaneous strain and temperature monitoring inside the composite material at cryogenic temperatures. The temperature sensitive polymer coating on an FBG sensor makes it a suitable candidate for cryogenic temperature measurement. The average temperature sensitivity of 48 pm °C−1 was obtained in −1180 ∼ 25 °C. In addition, the cross sensitivity problem has been adjusted by introducing a glass capillary tube to encapsulate the FBG. The thermal expansion of capillary material was compensated by cleaving the one end of FBG free and the other end with the temperature resistant epoxy resins. Experiments results validate that the proposed method can successfully monitor the strain and temperature factors that can be applied to composite material at cryogenic temperatures.

The Streicker Bridge at Princeton University campus has been equipped with two fiber-optic sensing technologies: discrete long-gauge sensing, based on Fiber Bragg-Gratings (FBG), and truly-distributed sensing, based on Brillouin Optical Time Domain Analysis (BOTDA). The sensors were embedded in concrete during the construction. The early age measurements, including hydration swelling and contraction, and post-tensioning of concrete were registered by both systems and placed side by side in order to compare their performances. Aside from the usual behavior, an unusual increase in strain was detected by several sensors in various cross-sections. The nature of this event is still under investigation, but preliminary study indicates early-age cracking as the cause. The comparison between the two monitoring systems shows good agreement in the areas where no unusual behavior was detected, but some discrepancies are noticed at locations where unusual behavior occurred and during the early age of concrete. These discrepancies are attributed to the spatial resolution of the distributed monitoring system and the temperature influences at early age. In this paper, general information concerning the Streicker Bridge project is given. The monitoring systems and their specifications are briefly presented. The monitoring data are analyzed and a comparison between the two systems is performed.

We demonstrate a new and simple configuration for measuring physical properties of liquids. With proper data analysis, the proposed setup can potentially extend its application to chemical analysis and characterization of two-phase fluids. The fiber sensor is based on the characteristic reflection spectrum obtained from different samples allocated on the tip of a cleaved single-mode optical fiber. Different tests fluids provide a distinctive reflection spectrum and the physical properties of the sample can thus be inferred through spectral analysis. Our experiments are based on a single mode optical fiber dipped into the liquid of interest and a fiber Bragg grating (FBG) interrogator for registering the backreflected light. We analyze how the pending drops formed on the tip of the fiber generate an interference pattern whose features depend on the physical properties of the test liquid. The experimental setup is controlled through a virtual instrument to perform the tests automatically. Each experiment involves data acquisition from the FBG interrogator and recording images by means of a CCD camera. Image analysis provides information about the geometry of the drop and fiber positioning is carefully controlled to provide consistent reflection patterns for different experiments with the same sample. Preliminary results show the correlation between the spectral response and the drop's geometry, which in turn is directly related to surface tension of the liquid sample. The performance of the proposed configuration is evaluated with two liquids (glycerin and PDMS polymer) showing the feasibility of this approach for developing a simple fiber optic liquid analyzer.