Fiber Optic Sensor Research Articles

A Highly Sensitive H-Shaped Optical Fiber Sensor for Monitoring Blood Glucose Level

A Highly Sensitive H-Shaped Optical Fiber Sensor for Monitoring Blood Glucose Level

Temperature-insensitive optical fiber sensor based on SMF-NCF-FMF-NCF-SMF spindle-shaped structure for refractive index measurement

Temperature-insensitive optical fiber sensor based on SMF-NCF-FMF-NCF-SMF spindle-shaped structure for refractive index measurement

Using orbital angular momentum for temperature and force sensing in an optical fiber

We demonstrate an optical fiber sensor that uses the orbital angular momentum of light in a polarization maintaining fiber to act as a temperature and force sensor. The polarization of the input light is shown to greatly affect the sensitivity of the sensor. In addition, we show how our sensor can be used to resolve the direction and magnitude of a force applied to a fiber.

Digital twin method for predicting the critical load of debonding damage in honeycomb sandwich structures based on distributed optical fiber sensor and Dynamic Bayesian Network

Digital twin method for predicting the critical load of debonding damage in honeycomb sandwich structures based on distributed optical fiber sensor and Dynamic Bayesian Network

Smart mechanoluminescent phosphors: A review of zinc sulfide‐based materials for advanced mechano‐optical applications

AbstractThe quest for mechanoluminescence (ML) in zinc sulfide (ZnS) spans more than a century, initially sparked by observations of natural minerals. There has been a resurgence in research into ML materials in recent decades, driven by advances in optoelectronic technologies and a deeper understanding of their luminescent properties under mechanical stress. ZnS, in particular, has garnered attention owing to its remarkable ability to sustain luminescence after more than 100,000 mechanical stimulations, positioning it as a standout candidate for optoelectronic applications. In contrast to conventional photoluminescent and electroluminescent light sources, ZnS composite elastomers have emerged as flexible, stretchable self‐powered light sources with considerable practical implications. This review introduces the development history, ML mechanisms, prototype ML devices, ZnS‐based ML material preparation methods, and their diverse applications spanning environmental mechanical‐to‐optical energy conversion, E‐signatures, anti‐counterfeiting, wearable information sensing devices, advanced battery‐free displays, biomedical imaging, and optical fiber sensors for human–computer interactions, among others. By integrating insights from ML‐optics, mechanics, and flexible optoelectronics, and by summarizing pertinent perspectives on current scientific challenges, application technology hurdles, and potential solutions for emerging scientific frontiers, this review aims to furnish fundamental guidance and conceptual frameworks for the design, advancement, and cutting‐edge application of novel mechanoluminescent materials.

Leakage monitoring of carbon dioxide injection well string using distributed optical fiber sensor

Whether the oil and gas fields in the Carbon Capture, Utilization, and Storage (CCUS) project use underground storage or energy supplementation to enhance oil recovery, they must be injected or monitored through the wellbore. Thus, the foundation and requirement for the safety of carbon dioxide (CO2) storage is the wellbore's integrity. When CO2 is dissolved in water, carbonic acid is created, and this acid strongly corrodes underground pipes. Therefore, the integrity issue with CO2 injection wells is more noticeable than with other wellbores. An annular pressure during gas injection is the primary symptom of gas injection string leakage in CO2 injection wells. This study aims to provide real-time pipe string monitoring using a distributed optical fiber temperature sensing system (DTS) and a distributed optical fiber acoustic sensing system (DAS). Variations in temperature and vibration are caused by annulus pressure relief or gas injection. Optical fiber logging, in contrast to traditional logging, has better performance indicators for optical fiber sensing apparatus. To adapt to complex wellbore conditions, it is necessary to enhance the temperature accuracy of DTS and the sensitivity and signal-to-noise ratio of DAS in CO2 drive injection wells based on the features of the gas injection string. To differentiate the leakage signal from the regular fluid flow signal, the energy calculation in the frequency band is done for DAS based on noise reduction, and the signal processing in the frequency band is done by the spectrum characteristics of the CO2 wellbore signal. The translation invariant wavelet algorithm is the primary denoising method for DTS, overcoming the shortcomings of traditional wavelet threshold algorithms such as excessive smoothing and the pseudo-Gibbs phenomenon. Furthermore, the depth correction during the optical cable lowering process is also examined in this paper. A CO2 gas injection well field experiment was conducted using this technology. A 1671m well was dug, and 1631m of optical cable were installed in the tubing. The tubing leakage position was successfully identified through gas injection, annulus pressure relief, and a comparison of DAS and DTS data. The field results demonstrate the accuracy with which the gas injection string integrity can be accurately monitored in real-time using distributed optical fiber sensing technology for CO2 injection wells.

Low-modal-crosstalk doped-fiber amplifiers in few-mode-fiber-based systems

Independent light propagation through one or multiple modes is commonly considered as a basic demand for mode manipulation in few-mode fiber (FMF)- or multimode fiber (MMF)-based optical systems such as transmission links, optical fiber lasers, or distributed optical fiber sensors. However, the insertion of doped-fiber amplifiers always kills the entire effort by inducing significant modal crosstalk. In this paper, we propose the design of doped-fiber amplifiers in FMF-based systems adopting identical multiple-ring-core (MRC) index profiles for both passive and doped fibers to achieve low modal crosstalk. We develop the direct-glass-transition (DGT) modified chemical vapor deposition (MCVD) processing for precise fabrication of few-mode erbium-doped fibers (FM-EDFs) with MRC profiles of both refractive index and erbium-ion doping distribution. Then, a few-mode erbium-doped-fiber amplifier (FM-EDFA) with a maximum gain of 26.08 dB and differential modal gain (DMG) of 2.3 dB is realized based on fabricated FM-EDF matched with a transmission FMF supporting four linearly polarized (LP) modes. With the insertion of the FM-EDFA, 60 + 60 km simultaneous LP01/LP11/LP21/LP02 transmission without inter-modal multiple-input multiple-output digital signal processing (MIMO-DSP) is successfully demonstrated. The proposed design of low-modal-crosstalk doped-fiber amplifiers provides, to our knowledge, new insights into mode manipulation methods in various applications.

A Novel Method for Integrity Assessment of Soil-Nailing Works with Actively Heated Fiber-Optic Sensors

A Novel Method for Integrity Assessment of Soil-Nailing Works with Actively Heated Fiber-Optic Sensors

Use of fiber-optic sensors to monitor concrete dams: recent breakthroughs and new opportunities.

Structural health monitoring of dams is a cornerstone tool for engineers to assess and ensure dam safety. One of the keystones of structural health monitoring is the acquisition of data with sensors to assess the overall health of the structure. Sensor technologies have experienced notable advances in recent years, such as the incorporation of devices based on fiber-optic technology. Here, we focus on the application of fiber-optic sensors (FOSs) to the monitoring of concrete dams. We review the literature and report the latest advances in fiber-optic technology available in the market as well as those used for research applications and compare the performance of FOSs with conventional devices and the requirements recommended by practitioners. FOSs have better performance than conventional sensors when it comes to monitoring most of the variables of interest to monitor concrete dams, such as temperature, strain, vibration, among others. Moreover, fiber-optic sensors have some inherent features that make them an excellent choice, such as high spatial resolution, easiness of data acquisition, or continuous spatial monitoring of parameters along the wire, among others.

Eigenfrequency analysis using fiber optic sensors and low-cost accelerometers for structural damage detection

Structural Health Monitoring (SHM) is crucial for infrastructure safety and integrity. Arduino-based sensors are gaining popularity in low-cost SHM structures. Distributed fiber optic systems (DFOS), such as Distributed Acoustic Sensing (DAS), are employed for accurate SHM despite their high costs, computational demands, and energy consumption. The primary objectives of this work are to compare the accuracy of an accelerometer named LARA (Low-cost Adaptable Reliable Accelerometer (LARA)) that utilizes both Arduino and Raspberry Pi technologies with a DAS system in detecting structural damage and to explore the potential advantages of combining LARA and DAS to create an effective SHM tool. This study is the first to enhance the design of LARA. Subsequently, LARA and DAS were used in a laboratory setting to analyze eigenfrequency changes in a beam model with induced localized damage. Finally, this study evaluated the precision and reliability of LARA and its potential role as a trigger for DAS in detecting localized damage. The findings show that both LARA and DAS can identify changes in the eigenfrequencies of damaged structures with deviations as small as 3.68 %. Consequently, LARA demonstrated its potential as a trigger for DAS, significantly reducing the computational demands while enriching the analysis. This approach offers highly accurate eigenfrequency measurements and enhances the analytical capabilities of DAS by identifying the primary axes of the detected eigenfrequencies.

Unpacking the packaged optical fiber bio-sensors: understanding the obstacle for biomedical application.

A biosensor is a promising alternative tool for the detection of clinically relevant analytes. Optical fiber as a transducer element in biosensors offers low cost, biocompatibility, and lack of electromagnetic interference. Moreover, due to the miniature size of optical fibers, they have the potential to be used in microfluidic chips and in vivo applications. The number of optical fiber biosensors are extensively growing: they have been developed to detect different analytes ranging from small molecules to whole cells. Yet the widespread applications of optical fiber biosensor have been hindered; one of the reasons is the lack of suitable packaging for their real-life application. In order to translate optical fiber biosensors into clinical practice, a proper embedding of biosensors into medical devices or portable chips is often required. A proper packaging approach is frequently as challenging as the sensor architecture itself. Therefore, this review aims to give an unpack different aspects of the integration of optical fiber biosensors into packaging platforms to bring them closer to actual clinical use. Particularly, the paper discusses how optical fiber sensors are integrated into flow cells, organized into microfluidic chips, inserted into catheters, or otherwise encased in medical devices to meet requirements of the prospective applications.

STRAIN TRANSFER ANALYSIS OF A FOUR-LAYER EMBEDDED FIBER OPTIC SENSING MODEL IN AN ELASTIC STATE

Optical fiber grating strain sensors are currently utilized in a variety of structural health monitoring applications. The encapsulated fiber optic sensor is unable to completely detect the strain of the structure, so the strain transfer theory should be established to maximize the strain sensing of fiber. It is required to explore the embedded four-layer fiber optic sensing model to create a more plausible strain transfer error hypothesis. Based on the three-layer fiber optic sensing model, the Goodman assumption and Fourier series approach were presented to study the strain transfer efficiency of the four-layer model in the elastic state. First, the physical quantity to be analyzed is determined, and finally the radius, interlayer bonding coefficient and elastic modulus are selected as the parameters affecting the strain transfer efficiency. The length range of efficiency evaluation is 0–2.5[Formula: see text]m, and the transfer efficiency under different radii is above 0.90 when the length [Formula: see text][Formula: see text]m. The interlayer bonding coefficient [Formula: see text] between [Formula: see text][Formula: see text]N/m3 and [Formula: see text][Formula: see text]N/m3 has little impact on the transfer efficiency, and the same is true for [Formula: see text], so it cannot be considered in practice. When [Formula: see text] is between [Formula: see text][Formula: see text]N/m3 and [Formula: see text][Formula: see text]N/m3 and the length [Formula: see text][Formula: see text]m, the strain transfer coefficient reaches 95%. The influence of elastic modulus on the transfer efficiency is very significant when [Formula: see text][Formula: see text]m. The four-layer model performs similarly to the three-layer model within the paste length range of 1.0[Formula: see text]m, but has a superior strain transfer effect when the pasted length exceeds 1.0[Formula: see text]m. As the radius of the protective layer rises, the effect of strain transfer deteriorates.

Time-resolved spectroscopic and SERS characterization of plasmonic optical fiber sensor using glutathione-capped gold nanourchins for detection of lead in water

Time-resolved spectroscopic and SERS characterization of plasmonic optical fiber sensor using glutathione-capped gold nanourchins for detection of lead in water

Evaluation of the fiber optic curvature sensor design parameters for new measurement approach application

In this paper, the influence of sensitive zone design parameters on the performance of fiber optic curvature sensor (FOCS) with sensitive zone made of V-grooves is experimentally investigated. A new insight into FOCS operation is given by introducing optical mode converter and CCD sensor into experimental setup, thus enabling mode-dependent analysis of V-grooves depth and spacing influence on sensor sensitivity and providing increased measurement reliability. Based on experimental analysis conducted in this work it is shown that FOCS intensity sensitivity increases approximately linear with sensitive zone depth and length, with highest sensitivity obtained for low order modes. According to this mode-dependent analysis, a new and more reliable measurement approach based on measurement of changes in the width of the output light distribution, rather than intensity, is proposed and tested. FOCS FWHM sensitivity increases approximately linear with depth and length of the sensitive zone, with higher sensitivity obtained in case of convex deformation. However, better linearity and balanced FWHM response is obtained for lower depths and shorter lengths of sensitive zone.

Microscopic Temperature Sensor Based on End-Face Fiber-Optic Fabry–Perot Interferometer

This work proposes a simple and affordable technology for the manufacturing of a miniature end-face fiber-optic temperature sensor based on a Fabry–Perot interferometer formed from a transparent UV-curable resin. For the manufactured working prototype of the sensor, the sensitivity and operating temperature range were determined, and the methods for their enhancement were proposed. Due to its small size, the proposed type of sensor can be used in high-precision and minimally invasive temperature measurements, in biology for microscale sample monitoring, and in medicine during operations using high-power lasers. A microwave photonic method is proposed that enables the interrogation of the sensor without using an optical spectrum analyzer.

Tapered fiber optic sensor for arterial pulse wave monitoring

Arterial pulse wave monitoring has been recognized as an effective medical diagnostic tool for various cardiovascular diseases. To overcome the barriers in traditional, complex, and expensive detection configurations, new electronic and optical sensors have been developed with their unique advantages. Particularly, various configurations of fiber-optic sensors have been proposed. This paper demonstrates the use of a tapered optical fiber structure to create a sensitive sensor that can detect carotid arterial pulse waves on the skin surface. The demonstrated fiber sensor probe utilizes an in-line Mach-Zehnder interferometer configuration and liquid-gold film coating on the sensor tip to enhance its sensitivity and demonstrate its use by encapsulating the sensor with a flexible elastomer material for detecting arterial pulse waves with a simple testing configuration. Considering the simple fabrication and high sensitivity without a complex demodulation scheme, the proposed sensor has broad implementation in biomedical health monitoring systems.

DASCore: a Python Library for Distributed Fiber Optic Sensing.

In the past decade, distributed acoustic sensing (DAS) has enabled many new monitoring applications in diverse fields including hydrocarbon exploration and extraction; induced, local, regional, and global seismology; infrastructure and urban monitoring; and several others. However, to date, the open-source software ecosystem for handling DAS data is relatively immature. Here we introduce DASCore, a Python library for analyzing, visualizing, and managing DAS data. DASCore implements an object-oriented interface for performing common data processing and transformations, reading and writing various DAS file types, creating simple visualizations, and managing file system-based DAS archives. DASCore also integrates with other Python-based tools which enable the processing of massive data sets in cloud environments. DASCore is the foundational package for the broader DAS data analysis ecosystem (DASDAE), and as such its main goal is to facilitate the development of other DAS libraries and applications.

Human Vital Signs Signal Monitoring and Repairment with an Optical Fiber Sensor Based on Deep Learning

Optical fiber sensors have been widely applied for their advantages such as small size, lightweight, and strong electronic interference robustness. Compared with current electronic sensors, optical fiber sensors perform better in measuring parameters in harsh environments, which makes them suitable for more and more applications, such as target tracing and detection and monitoring of health signs in medical services. However, due to fiber optic sensor failure, improper transmission and storage, or other reasons, missing data occur from time to time. Therefore, effective missing value processing methods are desirable as they can be used to facilitate data processing or analysis. In the present study, gated recurrent unit (GRU) interpolation is performed by using the generative adversarial network (GAN) model to process the irregular delay relationship between the data before and after the collection of incomplete vital signs data. Furthermore, a data interpolation model based on VS-E2E-GAN is proposed to reconstruct vital signs signals. The ROC curve (AUC), metrics including mean squared error (MSE), and accuracy (ACC) of experiments reach 0.901, 0.777, and 0.908, respectively, which indicates that the proposed VS-E2E-GAN model performs well in terms of vital signs data imputation and repairment, has strong robustness when compared with other works, and has potential clinical application in health monitoring, smart home, and so on.

Polyphenylene oxide based lossy mode resonance fiber sensor for the detection of volatile organic and inorganic compounds

This study presents the fabrication and characterization of a fiber optic gas sensor based on Lossy Mode Resonances (LMR). For the first time to our knowledge, a nanosized coating of polyphenylene oxide (PPO) is deposited on a cladding removed multimode silica fiber, serving both as the LMR supporting coating and sensitive overlay. The device exhibits a notable sensitivity of 2500 nm/RIU when immersed in glycerol-water based solutions. For gas detection, the PPO-based LMR device is exposed to varying concentrations of different volatile organic and inorganic compounds, including two alcohols (methanol and ethanol) and ammonia. The sensor demonstrates similar responses to methanol and ethanol gases with a sensitivity of about 0.56 nm/ppm and sensitivity of 0.25 nm/ppm to ammonia in the concentration range of 2.5–37.5 ppm, achieving limits of detection of a few ppm. To comprehensively evaluate the sensor performance, the investigation is also focused on the repeatability, reversibility, response times, as well as cross sensitivity to temperature and relative humidity.

Weakly coupled photonic flexible sensors based on sodium polyacrylate

The flexible optical fiber sensor serves as a prototype for highly sensitive photonic skin flexible sensors (PSFS) with rapid response times, facilitating the development of advanced wearable healthcare devices. Future bionic skin sensors, tailored for wearable devices focusing on health monitoring and robotics applications, will necessitate the incorporation of optical systems. In this work, PSFS based on weak coupling structure is proposed for the first time. This structure comprises a fiber optic sensor with weak coupling as the core sensing node, and the sensing material is hydrophilic and flexible sodium polyacrylate (SPA). The SPA combines the high sensitivity of PSFS with excellent biocompatibility, enabling both static and dynamic sensing measurements for physical parameters such as humidity and temperature. Leveraging the strain amplification effect of the single-mode tapered fiber and the unique fiber structure, the material's sensitivity to relative humidity (RH) is significantly enhanced, reaching 0.19 dB/%RH. Furthermore, the temperature response demonstrates exceptional sensitivity (0.29 dB/℃) within the range of human skin surface temperatures (30–48℃). Remarkably, the sensor has a significant response time of 128 ms. This research proposes a novel approach for constructing highly sensitive and versatile PSFS, which is critical for health care monitoring.