Fiber-optic Interferometer Research Articles

Integrated all-fiber-optic sensor based on FPI and MZI composite structures for temperature and strain measurement

In this paper, a temperature and strain sensor based on fiber-optic Mach-Zehnder interferometer (MZI) cascaded with Fabry-Perot interferometer (FPI) is designed and fabricated. The integrated sensor structure consists of no-core fiber (NCF) sandwiched by two sections of multi-mode fiber (MMF), hollow-core fiber (HCF), and two single-mode fibers (SMF) which are cascaded at the ends of the MMF and the HCF. Due to the thermal expansion effect, thermo-optic and elasto-optic effects of fiber material, the increase of the temperature and strain will make the change of the transmission mode, which will cause the spectral fringes wavelength shifting with strain, and the intensity of the spectral fringes varying with temperature but not strain variations in multiple temperature ranges. The series experiments valid show that the sensor with integrated structure realizes the strain and temperature measurements in multiple temperature ranges, and the minimum and maximum temperature sensitivities are − 0.278 dBm/°C and − 0.670 dBm/°C in the temperature range of 68–86 °C and 123–141 °C, respectively. The strain sensitivity is 2.17 pm/με all over the measured range. The integrated sensor structure has the advantages of high sensitivity, multiple measuring ranges, simple manufacturing, and low cost, which has the potential to be applied in the field of the internal strain and temperature measurements of different structures.

Quasi-distributed acoustic sensing based on optical path difference demodulation for high-frequency and large-amplitude using an optical fiber interferometer array.

The phase-sensitive optical time domain reflectometry scheme has attracted great research interest in distributed acoustic sensing (DAS) but suffers from a trade-off between the dynamic range and signal frequency. In this paper, an optical path difference (OPD) demodulation method is applied to an interferometer array composed of an ultra-weak fiber Bragg grating (UWFBG) array and an imbalanced Michelson interferometer to solve this problem. As far as we know, this is the first time that OPD demodulation has been applied to DAS. The UWFBG array is interrogated by a frequency-modulated pulse, and the acoustic signal sensed by the fiber between any two adjacent UWFBGs can be retrieved by demodulating the variation of residual OPD of the interferometer formed by them. The proposed method is analyzed theoretically and validated experimentally; compared with the phase demodulation method, a 100-times boost in bandwidth is achieved for a signal with an amplitude of 0.4 µε. Results also show that the proposed method offers increasing signal-to-noise ratios as the frequency increases.

Phase shift in optical fiber induced by mechanical stress

This work refers to the vibration optimization of a fiber optic interferometer whose detection performance may be compromised due to external mechanical or acoustic excitations. In such an interferometer, the optical path is split into two arms, with one significantly longer than the other. Optimizing the interferometer involves minimizing the phase difference of light caused by mechanical deformations, particularly in the long arm, resulting from unintended external excitations. Extending previous works from Hocker, who considered isotropic compression and longitudinal stress, we also investigate an additional mechanical load on the fiber: torsional stress. All these different loads will be compared to determine which one induces the most significant phase shift. Ultimately, incorporating protection into the equations will lead to a more realistic model. This approach will allow us to identify the most suitable protective materials to achieve a fiber optic interferometer resilient to external constraints.

Double-layer optical fiber interferometer with bio-layer-modified reflector for label-free biosensing of inflammatory proteins

This work discusses label-free biosensing application of a double-layer optical fiber interferometer where the second layer tailors the reflection conditions at the external plain and supports changes in reflected optical spectrum when a bio-layer binds to it. The double-layer nanostructure consists of precisely tailored thin films, i.e., titanium (TiO2) and hafnium oxides (HfO2) deposited on single-mode fiber end-face by magnetron sputtering. It has been shown numerically and experimentally that the approach besides well spectrally defined interference pattern distinguishes refractive index (RI) changes taking place in a volume and on the sensor surface. These are of interest when label-free biosensing applications are considered. The case of myeloperoxidase (MPO) detection—a protein, which concentration rises during inflammation—is reported as an example of application. The response of the sensor to MPO in a concentration range of 1 × 10−11–5 × 10−6 g/mL was tested. An increase in the MPO concentration was followed by a redshift of the interference pattern and a decrease in reflected power. The negative control performed using ferritin proved specificity of the sensor. The results reported in this work indicate capability of the approach for diagnostic label-free biosensing, possibly also at in vivo conditions.

Measurement of electron and neutral particle densities using a two-color optical fiber interferometer.

A two-color homodyne Mach-Zehnder optical fiber interferometer is developed for the measurement of electron and neutral particle densities in a high-density capsule θ-pinch device. The interferometer leverages the disparate contributions of distinct particles to the refractive index across two discrete wavelengths of 1310 and 1550nm and incorporates the contributions of both electron and neutral particle densities to the phase shift in the plasma. The temporal evolutions of line-integrated electron and neutral argon densities are successfully measured by the interferometer. Comparing the electron density waveforms under various working gas pressures as well as the results obtained using the monochromatic and two-color measurements, it is inferred that the influence of neutral particle density can be neglected when measuring the electron density using a long-wavelength laser. Moreover, the maximum electron density is linearly correlated with the capacitor bank voltage for the θ-pinch device (5-9kV). Overall, the proposed interferometer is capable of simultaneously measuring the electron and neutral particle densities.

A Hybrid GAN-Inception Deep Learning Approach for Enhanced Coordinate-Based Acoustic Emission Source Localization

In this paper, we propose a novel approach to coordinate-based acoustic emission (AE) source localization to address the challenges of limited and imbalanced datasets from fiber-optic AE sensors used for structural health monitoring (SHM). We have developed a hybrid deep learning model combining four generative adversarial network (GAN) variants for data augmentation with an adapted inception neural network for regression-based prediction. The experimental setup features a single fiber-optic AE sensor based on a tightly coiled fiber-optic Fabry-Perot interferometer formed by two identical fiber Bragg gratings. AE signals were generated using the Hsu-Nielsen pencil lead break test on a grid-marked thin aluminum plate with 35 distinct locations, simulating real-world structural monitoring conditions in bounded isotropic plate-like structures. It is demonstrated that the single-sensor configuration can achieve precise localization, avoiding the need for a multiple sensor array. The GAN-based signal augmentation expanded the dataset from 900 to 4500 samples, with the Wasserstein distance between the original and synthetic datasets decreasing by 83% after 2000 training epochs, demonstrating the high fidelity of the synthetic data. Among the GAN variants, the standard GAN architecture proved the most effective, outperforming other variants in this specific application. The hybrid model exhibits superior performance compared to non-augmented deep learning approaches, with the median error distribution comparisons revealing a significant 50% reduction in prediction errors, accompanied by substantially improved consistency across various AE source locations. Overall, this developed hybrid approach offers a promising solution for enhancing AE-based SHM in complex infrastructures, improving damage detection accuracy and reliability for more efficient predictive maintenance strategies.

DC current sensor based upon a fused fiber optic Fabry-Perot interferometer (FPI) and copper wire

In order to meet the demand for direct current (DC) current measurements in industrial production, a new type of fiber optic DC current sensor, combining thin copper wire and fiber optic Fabry-Perot interferometer (FPI), is reported. FPI is a sandwich structure formed by splicing a single-mode fiber (SMF) and a quartz capillary, with a cavity length of approximately 200 μm. The copper wire, with a length of 3.2 cm and a diameter of 1 mm, is attached to the FPI to form the sensor. Due to the excellent thermal conductivity of copper, the results showed that the sensor increased the sensitivity from 4.1 pm/°C to 11 pm/°C. After applying direct current to the sensor, a large quantity of heat generated by the copper wire was absorbed by the FPI, resulting in a significant shift in the resonant wavelength of FPI, which can indirectly measure the current. Three current experiments were performed, and parabolic curves have been used in fitting of the Dip wavelength and the square of the current. The results provide high correlation coefficients with values exceeding 0.99. Therefore, this curve may be used to measure the square of the current, further obtaining the current. In summary, the sensor is compact and durable, easy to manufacture, and provides high correlation coefficients, providing an alternative for measuring DC current.

Wavelength-Dependent Bragg Grating Sensors Cascade an Interferometer Sensor to Enhance Sensing Capacity and Diversification through the Deep Belief Network

Fiber-optic sensors, such as fiber Bragg grating (FBG) sensors and fiber-optic interferometers, have excellent sensing capabilities for industrial, chemical, and biomedical engineering applications. This paper used machine learning to enhance the number of fiber-optic sensing placement points and promote the cost-effectiveness and diversity of fiber-optic sensing applications. In this paper, the framework adopted is the FBG cascading an interferometer, and a deep belief network (DBN) is used to demodulate the wavelength of the sampled complex spectrum. As the capacity of the fiber-optic sensor arrangement is optimized, the peak spectra from FBGs undergoing strain or temperature changes may overlap. In addition, overlapping FBG spectra with interferometer spectra results in periodic modulation of the spectral intensity, making the spectral intensity variation more complex as a function of different strains or temperature levels. Therefore, it may not be possible to analyze the sensed results of FBGs with the naked eye, and it would be ideal to use machine learning to demodulate the sensed results of FBGs and the interferometer. Experimental results show that DBN can successfully interpret the wavelengths of individual FBG peaks, and peaks of the interferometer spectrum, from the overlapping spectrum of peak-overlapping FBGs and the interferometer.

Enhancing the sensitivity of a humidity sensor by using PVA and GQDs hybrid diaphragms and the harmonic Vernier effect

What we believe to be a novel fiber optic Fabry-Perot interferometer (FPI) humidity sensor based on polyvinyl alcohol (PVA) doped graphene quantum dots (GQDs) was proposed and experimentally studied. This sensor consisted of a sensing FPI and a reference FPI in parallel. The two sensing cavities FPI were composed of humidity sensitive materials PVA and PVA-GQDs, respectively. Experimental comparative studies had found that doping GQDs in PVA increases humidity sensitivity by 2.1 times. Four reference cavity FPIs were prepared by splicing single-mode fiber and quartz capillary, and then they were combined with two sensing cavity FPIs to form two Vernier effect (VE) sensors and two harmonic Vernier effect (HVE) sensors. Experimental research had found that the sensitivities of PVA as a sensing material for the VE sensor and HVE sensor were -1.0804 nm/%RH and-1.6566 nm/%RH, respectively. The sensitivities of PVA-GQDs as sensing materials for the VE sensor and HVE sensor were-3.1527 nm/%RH and 7.3343 nm/%RH, respectively. Moreover, both HVE sensors had minimal temperature crosstalk. PVA-GQDs were excellent humidity sensitive materials that significantly improve the sensitivity of humidity sensors, making it promising candidate for humidity sensing in various applications.

In situ monitoring of cycling characteristics in lithium-ion battery based on a two-cavity cascade fiber-optic Fabry-Perot interferometer

The state characterization inside the lithium-ion battery during charge/discharge cycling is extremely crucial for understanding the electrochemical reaction mechanism. However, current methods exhibit a challenge to overcome the specific battery environment obstacles, including strong redox properties, strong electromagnetic interference, and fast reaction processes. Hence, more efforts are still needed to monitor the actual state inside the battery accurately and reliably. To address this issue, we designed and developed a compact two-cavity cascade fiber-optic Fabry-Perot interferometer (FPI) sensor that can be safely implanted in batteries to measure internal temperature and pressure simultaneously. With its high pressure and temperature sensitivity of 26.6 ​nm/kPa and 107 ​nm/°C, this sensor exhibits an ultra-low cross-sensitivity of −40 ​Pa/°C. During charge/discharge cycling tests, regular cyclic pressure and temperature signals are obtained at various rates cycling in real-time and in situ, revealing details about the actual state characterization inside the battery. From the experiment results, the pressure inside the battery is divided into reversible changes caused by respiration effects and irreversible changes caused by trace gas production. Furthermore, the FPI sensor provides a more precise temperature than thermocouples that measure the surface temperature of the battery, reflecting the internal/external temperature difference to a maximum of 3.5 ​°C at 1 ​C rate cycling. This operando FPI sensor provides a valuable technological tool for battery performance testing and safety monitoring.

Dual-stage deep learning for sangac optical fiber sensing multi-event detection and localization

This paper introduces a dual-stage deep learning structure for multi-event detection and localization (DDMDL) for a loop-based Sagnac interferometer optical fiber sensing system to overcome the difficulties of detecting and localizing multiple events. The DDMDL approach comprises of a combination of (i) a detection stage made of a multi-class classification model that quantifies the events, and (ii) a localization stage made of separate deep-learning regression models tasked with precisely localizing the events. By addressing the multi-event localization as a combined multi-class classification and multi-regression problem, our approach enables more accurate prediction of event locations. We evaluate our DDMDL model in a broad range of test scenarios across three signal-to-noise ratio (SNR) levels: low, medium, and high, all outside the model’s training dataset. The model had high detection (i.e., classification) accuracy in simulation, with rates of 90%–99% for single-event scenarios, 94%–98% for two-event scenarios, and 82%–99% for three-event scenarios at the three SNR levels. The precision of localization (i.e., regression) was evaluated by Mean Absolute Error (MAE). The results showed that single-event scenarios could be localized within a range of 35–50 m, two-event scenarios within a range of 82–106 m, and three-event scenarios within a range of 131–151 m. These findings were consistent across different SNR levels, ranging from low to high, over a 50 km sensing fiber length. Experimental validations confirmed the DDMDL model’s practical applicability, with detection accuracy of 80% in single-event scenarios and localization accuracy with MAEs ranging between 32 and 65 m. For two-event scenarios, the model achieved an 87% success rate, with MAEs ranging between 122 m and 204 m, emphasizing the model’s potential effectiveness in different applications.

Multiplexing and passive demodulation of intrinsic low-finesse Fabry-Perot interferometers using free-running DFB diode lasers

This paper presents a novel and simple technique for passive quadrature demodulation of multiplexed low-finesse fiber-optic Fabry-Perot interferometers. The approach proposed here uses two quadrature channels with very close wavelengths generated by two thermostabilized DFB diode lasers operating in continuous-wave mode. A coherent light correlation technique was used to demultiplex the wavelength channels and signals from interferometers at different positions along the fiber. The proposed technique does not require optical filters for spectral channel demultiplexing, making it suitable for demodulating relatively long interferometers with any free spectral range. An in-line array of four identical 13.1 cm long interferometers was used to demonstrate the method's performance. Experimental results demonstrate a phase resolution of 1.38 phase degrees, corresponding to a temperature resolution of 3 × 10−3 °C. Numerical simulations indicate that the main factor limiting the length of the sensing interferometer, and thus the resolution of the system, is the wavelength variation of the temperature-stabilized, independently operating lasers. The number of spectral channels can be easily extended to realize three or four-wavelength demodulation schemes.

Research on the application of interferometric optical fiber sensors in high-pressure gas pipelines

The advantages of fiber optic sensors based on fiber optic interferometers with explosion-proof safety in gas pipeline monitoring has gradually emerged. A monitoring system for natural gas pipelines was designed and implemented using a Michelson interferometer as the core structure of the fiber optic sensor and processed the collected data using phase carrier generation demodulation algorithms. Addressing practical issues such as phase wrapping and arm length difference losses, an improved phase carrier demodulation algorithm based on tangent transformation and arctangent-differential self-cross-multiplication was proposed. Field experiments were conducted in gas valve chambers, to analyze the characteristics of leak signals in the pipeline. This study lays the foundation for the application of fiber optic interferometer sensors in gas pipeline monitoring, promising enhanced safety and efficiency.

An insight into the magneto-refractive effects of terbium-doped silica optical fibers used in magnetic field sensors

In this study, the magneto-refractive effect (MRE) of a terbium-doped fiber (TDF) that can be employed for magnetic field sensing was investigated. A microscopic model of a terbium doped magneto-refractive silica fiber was proposed, and the relationship between the refractive index (RI) of the fiber and its magnetic field was numerically studied. The MRE of the TDF was then characterized using an electronic holographic magneto-refractive measuring system. The characterization results showed that the RI of the TDF increased linearly at a rate of 2.13 × 10−5 RIU/mT as the magnetic field intensity increased from 0 to 10 mT. An all-solid-state magneto-refractive measurement system based on a fiber-optic Sagnac interferometer was designed for magnetic field sensing, which linearly responded to the applied magnetic field. The relationship between the dielectric tensor and magnetic moment of the fiber was analyzed. Based on the finite difference algorithm, the change in the RI and dielectric tensor of the optical fiber under a magnetic field was simulated. Results indicated that the proposed fiber has potential use in high-sensitive magnetic field sensing applications.

An ultra-sensitive photonic crystal fiber magnetic field sensor based on Vernier effect using two parallel Sagnac loops

Magnetic field detection is of significant importance in various fields, including military, industrial, and power transmission systems. In this paper, we propose a novel ultra-sensitive photonic crystal fiber (PCF) magnetic field sensor based on the Vernier effect, employing two parallel Sagnac loops. Since magnetic field detection relies on the magneto-optical effect of magnetic fluids, all air holes in the PCF are assumed to filled with magnetic fluids. By inserting two slightly different lengths of PCFs into two parallel Sagnac loops, the Vernier effect can be excited to improve the sensitivity of magnetic field detection. The sensing characteristics of the PCF magnetic field sensor are theoretically studied using the finite element method (FEM). Moreover, the influences of the wavelength and magnetic field intensity on the sensing performance are also analyzed. The results show that the sensitivity and resolution of the PCF magnetic field sensor can reach 11.9 nm Oe−1 and 8.4 × 10−3 Oe, respectively, within the magnetic field intensity range of 80–150 Oe. To our best knowledge, the proposed magnetic field sensor exhibits the highest sensitivity among existing magnetic field sensors based on optical fiber interferometers. The proposed magnetic field sensor possesses ultra-high sensitivity and resolution, which exhibits good application prospects in the field of magnetic field detection.

A Mach–Zehnder Fabry–Perot Hybrid Fibre-Optic Interferometer for a Large Measurement Range Based on the Kalman Filter

To solve the short working distance and small measurement range of an all-fibre interferometer, we proposed a Mach–Zehnder Fabry–Perot hybrid fibre-optic interferometry system based on sinusoidal phase modulation. In this paper, a low-finesse fibre interferometer with a larger linear operating range for displacement measurement is realised using a self-collimating probe and incorporating a Kalman filter-based phase demodulation algorithm. Through experimental comparisons, it is demonstrated that the interferometer proposed in this paper can effectively reduce the phase delay, compensate for the depth of modulation drift, and correct the error due to parasitic interference introduced by the optical path structure through the algorithm. A linear large measurement working range of 20 cm is realised.

Intermodal Fiber Interferometer with Spectral Interrogation and Fourier Analysis of Output Signals for Sensor Application

Interferometric fiber-optic sensors provide very high measurement accuracy and come with many other benefits. As such, the study of signal processing techniques for fiber-optic interferometers in order to extract information about external perturbation is an important area of research. In this work, the method of Fourier analysis was applied to extract information from the output signals of an intermodal fiber interferometer with spectral interrogation. It is shown that the external perturbation can be measured by obtaining the phase spectrum of the spectral transfer function of an intermodal fiber interferometer and determining the phase difference of a certain pair of mode groups. A mathematical model of this approach was developed, taking into account the parameters of the laser and the optical fiber, the number of excited mode groups, and the parameters of external perturbation. The theoretically considered method of Fourier analysis was experimentally verified, and it was proved to provide a linear response to external perturbation in a wide dynamic range.

High-speed PGC demodulation model and method with subnanometer displacement resolution in a fiber-optic micro-probe laser interferometer

As the key of embedded displacement measurement, a fiber-optic micro-probe laser interferometer (FMI) is of great interest in developing high-end equipment as well as precision metrology. However, conventional phase-generated carrier (PGC) approaches are for low-speed scenes and local error analysis, usually neglecting the global precision analysis and dynamic effect of system parameters under high-speed measurement, thus hindering their broad applications. We present a high-speed PGC demodulation model and method to achieve subnanometer displacement measurement precision in FMI. This model includes a global equivalent resolution analysis and revelation of the demodulation error mechanism. Utilizing this model, the failure issues regarding the PGC demodulation method under high speed and large range are addressed. Furthermore, an ultra-precision PGC demodulation algorithm based on the combination of static and dynamic delay adaptive regulation is proposed to enable high-speed and large-range displacement measurement. In this paper, the proposed model and algorithm are validated through simulation and experimental tests. The results demonstrate a displacement resolution of 0.1 nm with a standard deviation of less than 0.5 nm when measuring at a high velocity of 1.5 m/s—nearly a tenfold increase of the latest study.

Optical biosensing of monkeypox virus using novel recombinant silica-binding proteins for site-directed antibody immobilization

The efficient immobilization of capture antibodies is crucial for timely pathogen detection during global pandemic outbreaks. Therefore, we proposed a silica-binding protein featuring core functional domains (cSP). It comprises a peptide with a silica-binding tag designed to adhere to silica surfaces and tandem protein G fragments (2C2) for effective antibody capture. This innovation facilitates precise site-directed immobilization of antibodies onto silica surfaces. We applied cSP to silica-coated optical fibers, creating a fiber-optic biolayer interferometer (FO-BLI) biosensor capable of monitoring the monkeypox virus (MPXV) protein A29L in spiked clinical samples to rapidly detect the MPXV. The cSP-based FO-BLI biosensor for MPXV demonstrated a limit of detection (LOD) of 0.62 ng/mL in buffer, comparable to the 0.52 ng/mL LOD achieved using a conventional streptavidin (SA)-based FO-BLI biosensor. Furthermore, it achieved LODs of 0.77 ng/mL in spiked serum and 0.80 ng/mL in spiked saliva, exhibiting no cross-reactivity with other viral antigens. The MPXV detection process was completed within 14 min. We further proposed a cSP-based multi-virus biosensor strategy capable of detecting various pandemic strains, such as MPXV, the latest coronavirus disease (COVID) variants, and influenza A protein, to extend its versatility. The proposed cSP-modified FO-BLI biosensor has a high potential for rapidly and accurately detecting MPXV antigens, making valuable contributions to epidemiological studies.

Dual-Polarization Fiber Optic Differential Interferometer for High-Sensitivity Sensing Applications

Dual-Polarization Fiber Optic Differential Interferometer for High-Sensitivity Sensing Applications