Fiber Bragg grating sensing system for temperature measurements based on optically injected DFB-LD with an OEO loop.

A novel fiber Bragg grating (FBG) sensing system, based on an optically injected distributed feedback laser diode (DFB-LD) with an optoelectronic oscillating (OEO) loop, is proposed and experimentally demonstrated for temperature measurements with high and tunable sensitivity. The FBG sensor device works as an edge filter to adjust the optical power of the injected beam in response to temperature variations. The optically injected DFB-LD works at Period-one (P1) oscillating state, and the central wavelength of the oscillating mode of the DFB-LD can be tuned by the variable power of the injected beam. Furthermore, an OEO loop is implemented to improve the signal quality of the generated P1 microwave signal. Hence, the sensing parameter of temperature is converted to the frequency variation of the generated P1 microwave signal in the proposed sensing system. In the proof-of-concept experiment, a series of P1 microwave signals are generated while different temperatures are applied to the FBG sensor. The sensitivity of the proposed FBG sensing system for temperature measurements can be tuned from 0.44322 GHz/°C to 1.25952 GHz/°C. The stability and repeatability experiments are also performed, demonstrating the high measurement accuracy (0.0629°C) and low error of the system. The proposed FBG-based sensing and interrogation system exhibits high sensitivity, large tunability, good linearity, and flexible sensing generality.

Fast and robust demodulation of temperature from sparse sapphire fiber Bragg grating spectra with machine learning.

Sapphire fiber Bragg gratings (FBGs) have demonstrated their efficacy in sensing at high-temperature harsh environments owing to their elevated melting point and outstanding stability. However, due to the extremely high volume of modes supported by the clad-less sapphire fiber, the demodulation capability of the reflected spectra is hindered due to their irregular and somewhat complicated shapes. Hence, a mode-stripping or scrambling step is typically employed beforehand, albeit at the expense of sensor robustness. Additionally, conventional interrogation of sapphire FBG sensors relies on an optical spectrum analyzer due to the high sensitivity provided by the spectrum analyzer, where the long data acquisition time restricts the system from detecting instantaneous temperature variations. In this study, we present a simple sensor configuration by directly butt-coupling the sapphire FBG multi-mode lead-out fiber to a single-mode lead-in fiber, and detect its reflected spectra via a low-cost, fast, and coarsely resolved (166 pm) spectrometer. We leverage machine learning to compensate for the under-sampling of the measured FBG spectra and achieve a temperature accuracy of 0.23 °C at a high data acquisition rate of 5 kHz (limited by the spectrometer). This represents a tenfold improvement in accuracy compared to conventional peak-searching and curve-fitting methods, as well as a significant enhancement in measurement speed that enables dynamic sensing. We further assess the robustness of our sensor by attaching one side of the sensor to a vibrator and still observe good performance (0.43 °C) even under strong shaking conditions. The introduced demodulation technology opens up opportunities for the broader use of sapphire FBG sensors in noisy and high-temperature harsh environments.

Microwave-photonic Vernier effect enabled high-sensitivity fiber Bragg grating sensors for point-wise and quasi-distributed sensing.

This paper reports a sensitivity-improved fiber Bragg grating (FBG) sensor system based on microwave-photonic interferometry and the Vernier effect. An incoherent microwave photonics system based on a broadband light source is employed to interrogate the FBG sensor using the wavelength-to-delay mapping technique combined with interferometry. Specifically, the sensing FBG together with a reference FBG is used to construct a microwave photonics Michelson interferometer (MI). Changes in the Bragg wavelength of the sensing FBG subject to external perturbations are encoded into the spectral shifts of the microwave interferogram of the MI. A virtual interferometer is then generated from the sensing MI based on a computational Vernier effect modality. By superimposing the spectra of the sensing MI and the virtual interferometer, the Vernier effect is generated. By tracking the spectral shift of the Vernier envelope, it is shown that the measurement sensitivity of the sensing FBG is remarkably enhanced with an expected factor. Moreover, a quasi-distributed sensor system with enhanced sensitivity based on cascaded FBGs and the proposed virtual microwave-photonic Vernier effect technique is implemented, representing the first demonstration of a Vernier effect-enhanced FBG array sensor. Additionally, the possibility of employing the harmonic Vernier effect for further sensitivity enhancement is investigated, where a remarkable sensitivity enhancement factor up to 685 with a strain sensitivity of 94 MHz/µÎµ is successfully demonstrated.

Fs-Laser Fabricated Miniature Fabry-Perot Interferometer in a No-Core Fiber for High-Temperature Applications.

This paper reports a fiber in-line Fabry-Perot interferometer (FPI) fabricated in a no-core fiber using the direct femtosecond laser writing technique for high-temperature sensing applications. Two in-line reflectors are directly inscribed in a no-core fiber to construct a low-finesse FPI. Fringe visibility greater than 10 dB is obtained from the reflection spectra of the fabricated no-core fiber FPIs. Temperature responses of a prototype no-core fiber FPI are characterized up to 1000 °C. The proposed configuration is compact and easy to fabricate, making it attractive for sensing applications in high-temperature harsh environments.

Design and Development of Ultrabroadband, High-Gain, and High-Isolation THz MIMO Antenna with a Complementary Split-Ring Resonator Metamaterial.

The need for high-speed communication has created a way to design THz antennas that operate at high frequencies, speeds, and data rates. In this manuscript, a THz MIMO antenna is designed using a metamaterial. The two-port antenna design proposed uses a complementary split-ring resonator patch. The design results are also compared with a simple patch antenna to show the improvement. The design shows a better isolation of 50 dB. A broadband width of 8.3 THz is achieved using this complementary split-ring resonator design. The percentage bandwidth is 90%, showing an ultrabroadband response. The highest gain of 10.34 dB is achieved with this design. Structural parametric optimization is applied to the complementary split-ring resonator MIMO antenna design. The designed antenna is also optimized by applying parametric optimization to different geometrical parameters. The optimized design has a 20 µm ground plane, 14 µm outer ring width, 6 µm inner ring width, and 1.6 µm substrate thickness. The proposed antenna with its broadband width, high gain, and high isolation could be applied in high-speed communication devices.

Vernier effect-based optical fiber sensor for dynamic sensing using a coarsely resolved spectrometer.

Vernier effect-based optical fiber sensors have been demonstrated for high-sensitivity measurements of a diverse array of physical and chemical parameters. The interrogation of a Vernier sensor typically needs a broadband source and an optical spectrum analyzer to measure amplitudes over a broad wavelength window with dense sampling points, facilitating accurate extraction of the Vernier modulation envelope for sensitivity-improved sensing. However, the stringent requirement on the interrogation system limits the dynamic sensing capability of Vernier sensors. In this work, the possibility of employing a light source with a small wavelength bandwidth (35 nm) and a coarsely resolved spectrometer (∼166 pm) for the interrogation of an optical fiber Vernier sensor is demonstrated with the assistance of a machine learning-based analysis technique. Dynamic sensing of the exponential decay process of a cantilever beam has been successfully implemented with the low-cost and intelligent Vernier sensor. This work represents a first step towards a simpler, faster, and cheaper way to characterize the response of optical fiber sensors based on the Vernier effect.

A Design of a Novel Silicon Photonics Sensor with Ultra-Large Free Spectral Range Based on a Directional Coupler-Assisted Racetrack Resonator (DCARR).

A novel refractive index-based sensor implemented within a silicon photonic integrated circuit (PIC) is reported. The design is based on a double-directional coupler (DC) integrated with a racetrack-type resonator (RR) to enhance the optical response to changes in the near-surface refractive index via the optical Vernier effect. Although this approach can give rise to an extremely large 'envelope' free spectral range (FSRVernier), we restrict the design geometry to ensure this is within the traditional silicon PIC operating wavelength range of 1400-1700 nm. As a result, the exemplar double DC-assisted RR (DCARR) device demonstrated here, with FSRVernier = 246 nm, has a spectral sensitivity SVernier = 5 × 104 nm/RIU.

Machine learning for a Vernier-effect-based optical fiber sensor.

In recent years, the optical Vernier effect has been demonstrated as an effective tool to improve the sensitivity of optical fiber interferometer-based sensors, potentially facilitating a new generation of highly sensitive fiber sensing systems. Previous work has mainly focused on the physical implementation of Vernier-effect-based sensors using different combinations of interferometers, while the signal demodulation aspect has been neglected. However, accurate and reliable extraction of useful information from the sensing signal is critically important and determines the overall performance of the sensing system. In this Letter, we, for the first time, propose and demonstrate that machine learning (ML) can be employed for the demodulation of optical Vernier-effect-based fiber sensors. ML analysis enables direct, fast, and reliable readout of the measurand from the optical spectrum, avoiding the complicated and cumbersome data processing required in the conventional demodulation approach. This work opens new avenues for the development of Vernier-effect-based high-sensitivity optical fiber sensing systems.

Graphene oxide integrated silicon photonics for detection of vapour phase volatile organic compounds.

The optical response of a graphene oxide integrated silicon micro-ring resonator (GOMRR) to a range of vapour phase Volatile Organic Compounds (VOCs) is reported. The response of the GOMRR to all but one (hexane) of the VOCs tested is significantly higher than that of the uncoated (control) silicon MRR, for the same vapour flow rate. An iterative Finite Difference Eigenmode (FDE) simulation reveals that the sensitivity of the GO integrated device (in terms of RIU/nm) is enhanced by a factor of ~2, which is coupled with a lower limit of detection. Critically, the simulations reveal that the strength of the optical response is determined by molecular specific changes in the local refractive index probed by the evanescent field of the guided optical mode in the device. Analytical modelling of the experimental data, based on Hill-Langmuir adsorption characteristics, suggests that these changes in the local refractive index are determined by the degree of molecular cooperativity, which is enhanced for molecules with a polarity that is high, relative to their kinetic diameter. We believe this reflects a molecular dependent capillary condensation within the graphene oxide interlayers, which, when combined with highly sensitive optical detection, provides a potential route for discriminating between different vapour phase VOCs.