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The temperature response of pavement is not only crucial for assessing the internal stresses within pavement structures but is also an essential parameter in pavement design. Investigating the temperature response of rubberized concrete pavements (RCP) can support the construction of large-scale rubber concrete pavements. This study constructed a pavement monitoring system based on fiber Bragg grating technology to investigate the temperature distribution, temperature strain, temperature effects, and temperature stress of RCP. The results show that the daily temperature-time history curves of concrete pavement exhibit a significant asymmetry, with the heating phase accounting for only one-third of the curve. The temperature at the middle of RCP is 1.8 °C higher than that of ordinary concrete pavement (OCP). The temperature distribution along the thickness of the pavement follows a "spindle-shaped" pattern, with higher temperatures in the center and lower temperatures at the ends. Additionally, the addition of rubber aggregates increases the temperature strain in the pavements, makes the temperature-strain hysteresis effect more pronounced, and increases the curvature of the pavement slab. However, the daily stress range at the bottom of RCP is approximately 0.7 times that of OCP.

A two-stage decoupling model based on an artificial neural network with polynomial regression is proposed for the six-component force sensor load decoupling problem in the case of multidimensional mixed loading. The six-dimensional load categorization stage model constructed in the first stage combines 63 load category label sets with a deep BP neural network. The six-dimensional load regression stage model was constructed by combining polynomial regression with a BP neural network in the second stage. Meanwhile, the six-component force sensor with a fiber Bragg grating (FBG) sensor as the sensitive element was designed, and the elastomer simulation and calibration experimental dataset was established to realize the validation of the two-stage decoupling model. The results based on the simulation data show that the accuracy of the classification stage is 93.65%. The MAPE for the force channel in the regression stage is 6.29%, and 3.24% for the moment channel. The results based on experimental data show that the accuracy of the classification stage is 87.80%. The MAPE for the force channel in the regression phase is 5.63%, and 4.82% for the moment channel.

The additive noise in the condition monitoring system using fiber Bragg grating (FBG) sensors, including white Gaussian noise and multifrequency interference, has a significantly negative influence on the fault diagnosis of rotating machinery. Spectral subtraction (SS) is an effective method for handling white Gaussian noise. However, the SS method exhibits poor performance in eliminating multifrequency interference because estimating the noise spectrum accurately is difficult, and it significantly weakens the useful information components in measured signals. In this study, an improved spectral subtraction (ISS) method is proposed to enhance its denoising performance. In the ISS method, a reference noise signal measured by the same sensing system without working loads is considered the estimated noise, the same sliding window is used to divide the power spectrums of the measured and reference noise signals into multiple frequency bands, and the formula of spectral subtraction in the standard SS method is modified. A simulation analysis and an experiment are executed by using simulated signals and establishing a vibration test rig based on the FBG sensor, respectively. The statistical results demonstrate the effectiveness and feasibility of the ISS method in simultaneously eliminating white Gaussian noise and multifrequency interference while well maintaining the useful information components.

Weigh-in-motion (WIM) systems are essential for efficient transportation and monitoring parameters such as vehicle number, speed, and weight to ensure regulatory compliance and enhance road safety. Recently, WIM measurements using the Glass Fiber Reinforced Polymer Fiber Bragg Grating (GFRP-FBG) sensors have shown robustness and effectiveness. However, the accuracy of weight evaluation using the WIM systems based on GFRP-FBG sensors can be significantly influenced by the vehicle-wandering effect, which introduces uncertainties in wheel position determination and weight calculations. This paper assessed the impact of vehicle wandering on the accuracy of a WIM measurement system based on GFRP-FBG sensors by utilizing a new hybrid sensor-camera system that integrates roadside cameras and in-pavement GFRP-FBG sensors. The detailed methodology and framework of the developed hybrid system are introduced, followed by field testing on Highway I-94 in the United States. The field testing results indicate that by using the hybrid system, the wheel load detection accuracy of the WIM system based on GFRP-FBG sensors can be controlled to be a Type I or Type III WIM according to the ASTM 1318E-09 standard, with an average accuracy ranging from 87.83% to 94.65%. At the same time, when the wander distance is less than or equal to 9 cm, the developed WIM system proves to be very cost-effective as it only comprises two GFRP-FBG sensors, one temperature FBG sensor, and one camera. These findings indicate the practical potential to enhance the accuracy of WIM systems based on GFRP-FBG sensors designed for highways for low-coast, reliable, and accurate measurements by addressing vehicle wandering effects.

Lumbar puncture is a minimally invasive procedure that utilizes a spinal needle to puncture the lumbar epidural space to take a sample from the cerebrospinal fluid or inject drugs for diagnostic and therapeutic purposes. Physicians rely on their expertise to localize epidural space. Due to its critical procedure, the failure rate can reach up to 28%. Hence, a high level of experience and caution is required to correctly insert the needle without puncturing the dura mater, which is a fibrous layer protecting the spinal cord. Failure of spinal anesthesia is, in some cases, related to faulty needle placement techniques since it is blindly inserted. Therefore, advanced techniques for localization of the epidural space are essential to avoid any possible side effects. As for epidural space localization, various ideas were carried out over recent years to provide accurate identification of the epidural space. Subsequently, several methodologies based on mechanical and optical schemes have been proposed. Several research groups worked from different aspects of the problem, namely, the clinical and engineering sides. Hence, the main goal of this paper is to review this research with the aim of remedying the gap between the clinical side of the problem and the engineering side by examining the main techniques in building sensors for such purposes. This manuscript provides an understanding of the clinical needs of spinal needles from an anatomical point of view. Most importantly, it discusses the mechanical and optical approaches in designing and building sensors to guide spinal needles. Finally, the standards that must be followed in building smart spinal needles for approval procedures are also presented, along with some insight into future directions.

Epidural analgesia represents a clinical common practice aiming at pain mitigation. This loco-regional technique is widely used in several applications such as labor, surgery and lower back pain. It involves the injections of anesthetics or analgesics into the epidural space (ES). The ES detection is still demanding and is usually performed by the techniques named loss of resistance (LOR). In this study, we propose a novel soft system (SS) based on one fiber Bragg grating sensor (FBG) embedded in a soft polymeric matrix for LOR detection during the epidural puncture. The SS was designed to allow instrumenting the syringe's plunger without relevant modifications of the anesthetist's sensations during the procedure. After the metrological characterization of the SS, we assessed the capability of this solution in detecting LOR by carrying it out in silico and in clinical settings. For both trials, results revealed the capability of the proposed solutions in detecting the LOR and then in recording the force exerted on the plunger.

Joints between diaphragm wall panels are weak spots in wall construction. It is essential that potential leak sites are detected prior to excavation. In this study, a novel leak detection and monitoring system is presented that is based on fiber Bragg grating (FBG) sensing technology. A field study was performed in a deep excavation supported by diaphragm walls (in Hohhot, China) to validate the feasibility and effectiveness of the proposed method. Two schemes were trialed; one using pipes made of stainless steel, and one used a pipeless method. The results of the field study are presented and discussed. They show that potential leak sites in the wall joints could be determined prior to excavation using the proposed detection method. Stainless steel is a good material to use to make the detection tube because it can protect the FBG sensors and heating belts from damage and is more sensitive to water leakage. The field study provides good evidence for the feasibility of the new detection system. It also provides valuable experience for the field application of the system and has generated useful data to use in follow-up work.

The FBG (Fiber Bragg grating) sensor is an optical fiber type strain sensor. When a person breathes, strain occurs in the lungs and diaphragm. This was verified using an FBG sensor to which part of the living body this respiratory strain propagates. When measured in the abdomen, the signal waveforms were significantly different between breathing and apnea. The respiratory cycle measured by the temperature sensor attached to the mask and the strain cycle measured by the FBG sensor almost matched. Respiratory strain was measured in the abdomen, chest, and shoulder, and the signal amplitude decreased with distance from the abdomen. In addition, the respiratory rate could be calculated from the measured strain signal. On the other hand, respiratory strain did not propagate to the elbows and wrists, which were off the trunk, and the respiratory time, based on the signal period, could not be calculated at these parts. Therefore, it was shown that respiratory strain propagated in the trunk from the abdomen to the shoulder, but not in the peripheral parts of the elbow and wrist.

In order to examine the applicability of Fiber Bragg Grating (FBG) sensing technology in the static penetration of pipe piles, static penetration tests in clay were conducted using double-wall open and closed model pipe piles. The strain was measured using FBG sensors, and the plug height was measured using a cable displacement sensor. Using one open pile and two closed piles, the difference in pipe pile penetration was compared and analyzed. Based on FBG sensing technology and the strain data, the penetration characteristics of the pipe pile, such as axial force, lateral friction, and driving resistance were examined. Results showed that FBG sensing technology has superior testing performance for the pipe pile penetration process, can accurately reflect the strain time history of pipe piles, and can clearly reflect the penetration process of pipe piles with increasing penetration depth. In addition, the variation law of the characteristics of the jacked pile pile-soil interface was obtained. This test has significance for model tests and the engineering design of pipe piles.

The Chinese space station is designed to carry out manned spaceflight, space science research, and so on. In serious applications, it is a common operation to inject gas into the hull, which can produce strain of the bulkhead. Accurate measurement of strain for the bulkhead is one of the key tasks in evaluating the health condition of the space station. This is the first work to perform strain detection for the Chinese space station bulkhead by using optical fiber Bragg grating. In the period of measurements, the resistance strain gauge is used as the strain standard. The measurement error of the fiber optical sensor in the circumferential direction is very small, being less than 4.52 με. However, the error in the axial direction is very large with the highest value of 28.93 με. Because the measurement error of bare fiber in the axial direction is very small, the transverse effect of the substrate of the fiber optical sensor likely plays a role. The comparison of the theoretical and experimental results of the transverse effect coefficients shows that they are fairly consistent, with values of 0.0271 and 0.0287, respectively. After the transverse effect is compensated, the strain deviation in the axial detection is smaller than 2.04 με. It is of great significance to carry out real-time health assessment for the bulkhead of the space station.

Structure Health Monitoring is a topic of great interest in port structures due to the ageing of structures and the limitations of evaluating structures. This paper presents a cloud computing-based stability evaluation platform for a pier type port structure using Fiber Bragg Grating (FBG) sensors in a system consisting of a FBG strain sensor, FBG displacement gauge, FBG angle meter, gateway, and cloud computing-based web server. The sensors were installed on core components of the structure and measurements were taken to evaluate the structures. The measurement values were transmitted to the web server via the gateway to analyze and visualize them. All data were analyzed and visualized in the web server to evaluate the structure based on the safety evaluation index (SEI). The stability evaluation platform for pier type port structures involves the efficient monitoring of the structures which can be carried out easily anytime and anywhere by converging new technologies such as cloud computing and FBG sensors. In addition, the platform has been successfully implemented at “Maryang Harbor” situated in Maryang-Meyon of Korea to test its durability.

Embedded fiber Bragg grating sensors have been extensively used worldwide for health monitoring of smart structures. In civil engineering, they provide a powerful method for monitoring the performance of composite reinforcements used for concrete structure rehabilitation and retrofitting. This paper discusses the problem of investigating the strain transfer mechanism in composite strengthened concrete beams subjected to three-point bending tests. Fiber Bragg grating sensors were embedded both in the concrete tensioned surface and in the woven fiber reinforcement. It has been shown that, if interface decoupling occurs, strain in the concrete can be up to 3.8 times higher than that developed in the reinforcement. A zero friction slipping model was developed which fitted very well the experimental data., Competing Interests: The authors declare no conflict of interest.

We propose and demonstrate a fiber Bragg grating (FBG) sensor network employing the code division multiple access (CDMA) technique to identify information from individual sensors. To detect information without considering time delays between sensors, a sliding correlation method is applied, in which two different signals with the same pseudo-random binary sequence (PRBS) pattern, but slightly different frequencies, are applied to the source and detector sides. Moreover, for time domain detection, a wavelength-to-time conversion technique using a wavelength dispersive medium is introduced. The experimental results show that the proposed sensor network has a wide strain dynamic range of 2,400 με and a low crosstalk of 950:1.