Fiber Sensor Research Articles

An Intensity-Variation RI Sensor for Multi-Variant Alcohol Detection with Twisted Structure Using Polymer Optical Fiber

This research introduces an RI sensor for detecting various alcohol species with a designed twisted polymer optical fiber (POF) sensor. The sensor is developed via a straightforward twisting technique to form an effective coupling mechanism. The sensor works on intensity variation where coupled intensity varies when different types of alcohol are added. The structure relies on the twisting of two fibers, where one fiber is used as the illuminating fiber and the other fiber is used as the receiving fiber. Five different types of alcohol are tested (methanol, ethanol, propanol, butanol, and pentanol) as a substant. The experimental results reveal that the sensor is able to detect all five distinct substants effectively by optical power intensity variation. Moreover, the sensor’s sensitivity is analyzed with different factors such as the influence of the bending radius and the coupling length, which reveals that the sensing parameters could be customized depending on specific requirements. The sensor demonstrated consistent responses in repeatability tests, with minimal variation across multiple measurements, highlighting its stability. Additionally, the study explores temperature’s influence, revealing a sensitivity shift for every degree Celsius of change. This POF-based alcohol sensor represents a significant leap forward in optical sensing technology.

Deep learning and time series signal processing for bending detection in mining environment using optical fiber sensor

Optical fiber sensors are widely used to monitor environmental disturbances that may trigger or affect mining landslides, a complex phenomenon that involves various factors and can cause severe damage. In this study, we propose a method to detect the curvature of a bent optical fiber, which affects the optical signals traveling through it, using deep learning and time series signal processing. We use a Mach-Zehnder interferometer (MZI) sensor and a single-mode fiber (SMF) cable to capture the interference signal caused by different bending angles. We apply a transformation random convolutional kernel (TRANCE) to reduce the signal and extract its mean and standard deviation as features. We train a dense neural network (DNN) with three hidden layers to classify the bending events into four categories: low, medium, high, and extreme. We evaluate our method on a dataset of 400 samples and achieve an average accuracy of 99% in the confusion matrix and the fifty times tenfold validation experiments. Our method outperforms other methods that use multimode fiber (MMF), speckle images, and convolutional neural networks (CNNs) in terms of accuracy, speed, and generalization. Our method also has the advantages of using SMF, which enables integrated sensing and communication, and using 1D signals, which are easier to process than 2D images. Our method is suitable for high-speed signals containing information in dangerous environments.

Probe-type optical fiber sensors for electric field distribution measurement

This paper reports a compact fiber optical electric field (E-field) sensor aiming for the precise detection of transient E-field distributions. Here, a reflective polarization-reciprocal optical path is proposed, which inherently mitigates the temperature-induced birefringence interference of the electro-optical crystal without the need for additional optical elements, thereby facilitating a reduced-size sensing probe. Furthermore, an adaptive particle swarm optimization (A-PSO) algorithm has been utilized for the first time to optimize the insulation structure of the optical E-field sensor, which significantly suppresses field distortion within the sensing region by 50%. This method addresses the technical gap in optical E-field sensor structure optimization, providing an effective means to improve its spatial resolution. The experimental results demonstrate that the proposed sensor exhibits a broad response frequency range from 50 Hz to 15 MHz, with a sensitivity of 0.675 V/kV cm−1. The proposed sensor successfully monitors the spatial distribution of electric fields in the lightning interception region of a lightning rod, thereby validating its effectiveness.

Condensation heat transfer and applicability assessment of a printed circuit heat exchanger as a condenser in a cryogenic CO2 capture and storage system

Global warming is accelerating due to the rapid increase in CO2 emissions and cold energy. CO2 capture and storage systems (CCSSs) using discarded cold energy have been suggested to prevent this problem. To utilize cold energy, a printed circuit heat exchanger (PCHE) with high structural integrity was applied as a condenser in the CCSS. However, studies on condensation heat transfer in PCHE are still lacking, and conventional condensation heat transfer correlations developed in circular-channels do not sufficiently predict heat transfer performance in PCHE. Additionally, evaluating the local heat transfer performance is difficult because PCHE is an all-in-one type heat exchanger. Therefore, in this study, a CO2 condensation experiment in PCHE was conducted using an optical fiber sensor as a measurement, which can evaluate the local heat transfer performance, and a new condensation heat transfer correlation for CO2 in PCHE was developed. The correlation was approximately 20 % smaller than the conventional correlations developed in circular-channels, indicating that CO2 would not be fully condensed if the condenser was designed by conventional correlations. Based on the developed correlation, in-house code was developed and the CCSS using cold energy was compared with the conventional CCSS, which condenses CO2 after pressurizing it to a high pressure. As a result, cold energy based CCSS could replace the conventional CCSS because the CCSS using cold energy was approximately 5.7 million-USD per year more economical than the conventional CCSS when condensing CO2 at 200 tons/h. These results contribute to the design of PCHE-type condensers used in the CCSS.

Design and simulation of a highly sensitive photonic crystal fiber sensor for malaria detection

This research focuses on developing an innovative optical sensor utilizing photonic crystal fiber with a unique cladding structure. The photonic crystal fiber’s cladding consists of four layers of circular air holes, with two of them filled with hemoglobin. This arrangement renders the photonic crystal fiber sensitive to changes in hemoglobin concentration, primarily investigating its impact on chromatic dispersion – the wavelength-dependent refractive index variation. The study analyzes two specific wavelengths, 1.2 µm and 1.4 µm, finding high sensitivity at 1.2 µm, calculated to be 0.232 ps/(nm·km)/(g/L). The potential application lies in malaria diagnosis through non-invasive blood sample analysis. We selected the refractive index of an infected red blood cell at the ring stage, setting it at n = 1.395. Our proposed sensor demonstrates outstanding performance in diagnosing malaria at an HGB concentration of 38 g/L at 1.2 µm and at an HGB concentration of 40 g/L at 1.4 µm. By monitoring hemoglobin concentration changes, this photonic crystal fiber-based sensor offers a promising method for early and accurate malaria detection, thus potentially improving global healthcare.

Respiratory Rate Monitoring via a Fibre Bragg Grating-Embedded Respirator Mask with a Wearable Miniature Interrogator

A respiration rate (RR) monitoring system was created by integrating a Fibre Bragg Grating (FBG) optical fibre sensor into a respirator mask. The system exploits the sensitivity of an FBG to temperature to identify an individual’s RR by measuring airflow temperature variation near the nostrils and mouth. To monitor the FBG response, a portable, battery-powered, wireless miniature interrogator system was developed to replace a relatively bulky benchtop interrogator used in previous studies. A healthy volunteer study was conducted to evaluate the performance of the developed system (10 healthy volunteers). Volunteers were asked to perform normal breathing whilst simultaneously wearing the system and a reference spirometer for 120 s. Individual breaths are then identified using a peak detection algorithm. The result showed that the number of breaths detected by both devices matched exactly (100%) across all volunteer trials.

Highly sensitive photonic crystal fiber sensor for detection of hemoglobin and sucrose concentration

Abstract In this research, a flower-shape photonic crystal fiber sensor is proposed and designed. In this sensor, the most electromagnetic field is concentrated in the core part of the flower causing a surprising increase in the sensitivity of the sensor. Gold is used as a plasmonic material for stability in the environment. The analyte is placed outside the sensor and it makes the possibility of fabrication simple. The geometrical parameters of the sensor are optimized with the Nelder Mead algorithm. The detection power of the sensor is in the bio range and in this research, it is proposed to determine the concentration of sucrose and the concentration of hemoglobin. Taking advantage of the amazing geometry of nested circles to confine the electromagnetic field in the center of the fiber and increase the sensitivity of the sensor is a significant achievement. Using the optimal algorithm for design leads to the adaptation of the optimal geometry and the efficient construction of the sensor. The results show an excellent amplitude sensitivity of 5285 (RIU−1) and a suitable wavelength sensitivity of 11000 (nm RIU−1).

Advanced functional optical fiber sensors for smart battery monitoring

Advanced functional optical fiber sensors for smart battery monitoring

Simultaneous measurement of liquid refractive index and temperature based on the birefringence response of a water-filled D-shaped photonic crystal fiber

In this paper, a water-filled D-shaped photonic crystal fiber (WFDSPCF) sensor based on the birefringence response for simultaneously measuring the liquid refractive index (LRI) and liquid temperature (LT) is proposed. We undertake theoretical and simulation calculations, and the results show that the proposed WFDSPCF can achieve ultrahigh LRI and LT sensitivities when operating around the group birefringence turning point. By optimizing the structural parameters, the proposed WFDSPCF sensor can achieve LRI and LT sensitivities of -25642.86 nm/RIU and 12.8 nm/°C, respectively. In addition, in order to eliminate the sensing crosstalk between the LRI and LT, a parallel Lyot interferometer structure is also proposed. The proposed WFDSPCF sensor is expected to have potential use in biochemical sensing, measurement science, and environmental monitoring.

A Miniaturized Flexible Patch Based on CNT Fiber Sensors and Highly Integrated SoC for Analysis of Sweat

A Miniaturized Flexible Patch Based on CNT Fiber Sensors and Highly Integrated SoC for Analysis of Sweat

A Method for Improving Performance of Vector Bending Fiber Sensor Based on LSTM

A Method for Improving Performance of Vector Bending Fiber Sensor Based on LSTM

Projection to latent structures regression and its application to Mach–Zehnder interferometer optical fiber sensors for acetone detection

The techniques of multivariate analysis methods as prediction models open a new vision to the analysis of applied data. The method used in this work was projection to latent structures regression, which is a regression method that uses the latent variables generated by calculating the linear relationship between the dependent and independent variables giving them equal importance and thus obtaining the maximum variance and correlation of these variables. This method was applied to optical fiber sensors for acetone detection. It is important to detect acetone because it is a biomarker of diabetes mellitus. The sensor was fabricated with two cascaded long-period fiber gratings (LPFG) with a 515 µm grating period and separated 1 cm to form a Mach–Zehnder interferometer (MZI). Clinical studies for the diagnosis of diabetes are usually invasive, the development of these sensors proposes a new non-invasive option through the detection of acetone in human breath whose concentrations are in the order of 1.25–2.5 ppm. To study the response of the sensors to acetone, different sensing films, such as polydimethylsiloxane (PDMS), polymethyl methacrylate, Apiezon L and Apiezon T were used, which have a good affinity to this compound. Spectral changes in the transmission spectrum of the MZI were obtained due to the modes interference together with an increment of the sensitivity, since the interaction between the acetone concentration and the sensing film provokes a change in the effective index of the cladding, which in turn is amplified by the LPFGs separation. The analysis showed that the best results were obtained for the sensor with PDMS as sensing film, with the lowest limit of detection, 1.7 ppm using 4 latent structures.

Fabrication of hydrogen gas sensor using sputtered palladium-copper composite on tapered optical fiber

Abstract In this study, we fabricated a hydrogen (H2) gas sensor based on tapered optical fiber using sputtering method. Also, as the first attempt, we explored how palladium (Pd) and palladium-copper (Pd-Cu) coatings, deposited using the sputtering method (RF and DC), affect tapered optical fibers as H2 gas sensors (ranging from 1 to 8% H2). It investigates changes in sensor output power, response and recovery times, and the influence of fiber tapering angle on output power. The investigation reveals that two main factors, including permeability and elasto-optic effect significantly impact the results. At H2 concentrations of 1 to 3%, permeability predominantly affects Pd sensors, yielding better output power changes and sensitivity than Pd-Cu tapered optical fiber sensors. Conversely, at higher H2 concentrations (4 to 8%), the dominant factors appear to be permeability as well as elasto-optic effect. These characteristics have a greater influence in the Pd-Cu layer at higher H2 concentration, resulting in smoother slope in response to H2. Due to higher permeability, Pd sensors reach saturation faster, while Pd-Cu sensors exhibit more linear changes with increasing H2 levels and do not saturate like Pd sensors very fast. Moreover, the study shows that a larger tapering angle can enhance the output power of Pd-Cu tapered optical fiber sensors.

Seven-Core Fiber Composite Structures-Based Mach-Zehnder Interferometer for Bending and Temperature Measurement

In the paper, an optical fiber sensor based on a seven-core fiber composite structure is presented, which enables dual-parameter sensing of bending and temperature. The proposed structure is fabricated by combining the strongly-coupled seven-core fibers (SC-SCFs) and a weakly-coupled seven-core fiber (WC-SCF). The SC-SCF acts as a beam coupler and enhances the Mach-Zehnder interference, while the WC-SCF serves as the enhanced section of another Mach-Zehnder interference. Therefore, the spectrum response of the fiber structure mentioned above exhibits a superposition effect of two Mach-Zehnder interferometers (MZIs). Among them, two dips corresponding to different MZIs are used to measure bending and temperature. The experimental results show the bending sensitivity and temperature sensitivity of the two MZIs are −4.238 nm/m−1, −2.263 nm/m−1, 0.047 nm/°C, and 0.064 nm/°C, respectively. It proves that our sensor is very sensitive to bending. Through the dual-wavelength matrix method, the bending and temperature can be measured simultaneously. With the benefit of the composite structure, low cost, and ease of fabrication, the proposed sensor can be used in harsh environments.

Stretchable and High-Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring.

Electronic textiles with remarkable breathability, lightweight, and comfort hold great potential in wearable technologies and smart human-machine interfaces. Ionic capacitive sensors, leveraging the advantages of the electric double layer, offer higher sensitivity compared to traditional capacitive sensors. Current research on wearable ion-capacitive sensors has focused mainly on two-dimensional (2D) or three-dimensional (3D) device architectures, which show substantial challenges for direct integration with textiles and compromise their wearing experience on conformability and permeability. One-dimensional (1D) stretchable fiber materials serve as vital components in constructing electronic textiles, allowing for rich structural design, patterning, and device integration through mature textile techniques. Here, a stretchable functional fiber with robust mechanical and electrical performances is fabricated based on semi-solid metal and ionic polymer, which provided a high stretchability and good electrical conductivity, enabling seamless integration with textiles. Consequently, high-performance stretchable fiber sensors are developed through different device architecture designs, including pressure sensors with high sensitivity (7.21kPa-1), fast response (60ms/30ms), and excellent stability, as well as strain sensors with high sensitivity (GF = 1.05), wide detection range (0-300% strain), and excellent sensing stability under dynamic deformations.

An FBG-based method for load measurement of a cylindrical rolling element bearing

Abstract Contact forces between raceways and rolling elements of a bearing stand as crucial operational aspects defining the bearing’s performance. While monitoring bearing load through load cells or strain gauges on the shaft or housing is feasible, it may not precisely reflect the distributed load transmitted by the rollers directly to the raceways. This paper introduces a method to calculate these contact forces, relying on a linear assumption correlating the loads to the measured strains on the outer race of a bearing. In our research, we conducted both static and dynamic tests on cylindrical roller bearings through simulations and experiments. We designed an experimental test rig to conduct both static and dynamic experiments and utilized FBG optical fiber sensors for contact force measurement in bearings due to their multiple advantages, including high sensitivity, resistance to corrosion and magnetic interference, and ease of installation on the bearing outer race due to their shape and size. Our findings indicate a consistent linear relationship between contact forces and strains measured on the bearing’s outer race. Furthermore, we calculated the linear coefficient K values from three test groups: static tests under simulation study, static tests under experimental study, and dynamic tests under experimental study. The K values obtained from static tests (simulation and experimental studies) and dynamic tests (experimental study) align consistently. Following this, we calculated contact forces in both static and dynamic experiments by multiplying the measured strains with K. Our calculations resulted in an error percentage of less than 2% for static tests and below 5% for dynamic tests, highlighting the accuracy of our approach in determining these contact forces.

Fiber-Optic Sensor Spectrum Noise Reduction Based on a Generative Adversarial Network.

In the field of fiber-optic sensing, effectively reducing the noise of sensing spectra and achieving a high signal-to-noise ratio (SNR) has consistently been a focal point of research. This study proposes a deep-learning-based denoising method for fiber-optic sensors, which involves pre-processing the sensor spectrum into a 2D image and training with a cycle-consistent generative adversarial network (Cycle-GAN) model. The pre-trained algorithm demonstrates the ability to effectively denoise various spectrum types and noise profiles. This study evaluates the denoising performance of simulated spectra obtained from four different types of fiber-optic sensors: fiber Fabry-Perot interferometer (FPI), regular fiber Bragg grating (FBG), chirped FBG, and FBG pair. Compared to traditional denoising algorithms such as wavelet transform (WT) and empirical mode decomposition (EMD), the proposed method achieves an SNR improvement of up to 13.71 dB, an RMSE that is up to three times smaller, and a minimum correlation coefficient (R2) of no less than 99.70% with the original high-SNR signals. Additionally, the proposed algorithm was tested for multimode noise reduction, demonstrating an excellent linearity in temperature response with a R2 of 99.95% for its linear fitting and 99.74% for the temperature response obtained from single-mode fiber sensors. The proposed denoising approach effectively reduces the impact of various noises from the sensing system, enhancing the practicality of fiber-optic sensing, especially for specialized fiber applications in research and industrial domains.

Measurement of dynamic deformation during shock loading using a fiber-optic loop-sensor

Abstract Characterizing materials under shock loading has been of interest in fields such as protective material development, biomechanics to study the injury mechanics and high-speed aerodynamic structures. However, shock loading of material is a very short duration phenomenon and it is extremely challenging to develop sensors for dynamic measurements under such loading conditions. Optical fiber sensors that present the possibilities to allow high resolution measurement of force or displacement in such high strain rate loading conditions. This work studies the possibility of developing a single mode optical fiber sensor based on the principle of power losses from the curved section for dynamic measurements under shock loading conditions. The strain measurement results obtained from the optical sensors are validated with the controlled digital image correlation measurements are found to be in close correlation. The sensor was able to provide time sensitivity of better than 1 ms. The results show that the fiber sensor has the characteristics of high sensitivity and high precision, which can be used to measure fine vibration in real-time.

Tapered coreless optical fiber-based refractive index sensor for acetone concentration detection

A fast-response optical fiber sensor is designed and fabricated to detect different concentrations of volatile acetone. The proposed sensor structure was fabricated by splicing a segment of tapered coreless fiber (CLF) amid two single-mode fibers (SMF). Herein, tuned tapered diameters and lengths of CLF’s cladding were immersed in various concentrations of the acetone solutions to sense the effective refractive index (RI) variations. Accordingly, the sensor’s performance with tuned diameters at different lengths of the CLF was optimized to realize the suitable size of amplified evanescent fields. The sensor responded remarkably towards acetone concentrations, with a superior sensitivity of 336.102 nm/RIU, 0.163 nm/%, and 27.531 × 10−5 nm/ppm at 5 cm length and 60 µm taper diameter of CLF. The examined sensor possesses a fast response time with a minimum detection limit of 0.244 RIU, 5.025%vol, and 2.9 ppm. Though the rapid evaporation (volatility) of the acetone compound exempted it from air pollutants, many industrial and human body processes produce acetone which needs to be detected. The examined sensor may have the potential to detect in a non-invasive approach with high accuracy and rapid diabetes in humans, lung cancer, etc.

Strain-insensitive fiber sensors bioinspired by spider silk with a multilevel helical structure

The emergence of wearable electronics has greatly stimulated the exploration of fibers due to their inherent wearing comfort. However, the manufacturing of conductive fibers with both exceptional mechanical strength and stable conductive properties remains a formidable challenge. Inspired by the helical structure of spider silk, we propose a strain-insensitive conductive fiber with a multilevel helical structure by helically arranging carbon fibers on the surface of helical polyurethane nanofibers, which is further employed in the fabrication of fiber sensors. The resulting fibers demonstrate outstanding strain stability with a resistance change rate (ΔR/R0) of less than 0.09 when the strain reaches 100% and a resistance change rate below 0.3 at the 200% strain level, significantly outperforming previous reports. Through experimental investigations and computational analysis, we elucidate that the underlying mechanism of the superior conductive performance and stability is attributed to the redundant helical structures and polyurethane nanofiber core layer contraction. Moreover, the fiber devices fabricated on the basis of our strain-insensitive conductive fibers exhibit distinguished performance in various health-related physiological signal monitoring tasks, such as respiration heat monitoring, voice recording, and electrochemical detection of sweat constituents.