Search Results (2,751)

This paper presents a novel lightweight fabric strain sensor array specifically designed for comprehensive knee joint monitoring. The sensor system features a unique two-layer design incorporating eight strategically positioned sensing elements, enabling effective spatial mapping of strain distribution across the knee during movement. This configuration offers advantages in capturing complex multi-axis kinematics (flexion/extension, rotation) and localized tissue deformation when compared to simpler sensor layouts. To evaluate the system, ten subjects performed three distinct activities (seated leg raise, standing, walking), generating resistance data from the sensors. A hybrid deep learning model (CNN + BiLSTM + Attention) processed the data and significantly improved performance to 95%. This enhanced accuracy is attributed to the model’s ability to extract spatial-temporal features and leverage long-term dependencies within the time-series sensor data. Furthermore, channel attention analysis within the deep learning model identified sensors 2, 4, and 6 as major contributors to classification performance. The results demonstrate the feasibility of the proposed fabric sensor array for accurately recognizing fundamental knee movements. Despite limitations in the diversity of postures, this system holds significant promise for future applications in rehabilitation monitoring, sports science analytics, and personalized healthcare within the medical and athletic domains. Full article

Electrical strain gauges are essential for monitoring wind turbine tower loads and fatigue, but accurate load measurements from these sensors require calibration over time to correct the zero-drift found in long-term measured signals. Calibration is often performed using nacelle rotation events for cable untwisting, where the tower mechanical load is known; however, non-uniform solar heating during these events can introduce thermal stresses that are misinterpreted as drift, causing systematic errors. This study evaluates six preprocessing methods for correcting zero-drift and thermal stresses in strain gauges, using measurements from two tower cross-sections—one with temperature sensors and one without. Performance is quantified using the scatter of the 10 min mean bending moments in the fore–aft and side-to-side directions and the cumulative fatigue damage over the monitoring periods. Results show that modelling the thermal stresses using a linear regression model with temperature measurements as inputs yields the most physically consistent load curves. If temperature measurements are unavailable, the effects of thermal stresses can be partly mitigated by restricting calibration to nighttime events or using solar-position variables in a regression model (instead of temperatures). As expected, the choice of preprocessing method significantly impacts load curves, but its influence on fatigue damage estimates is limited. Full article

The large-scale deployment of aerospace composite structures has become a defining trend in modern aeronautics; however, hidden damage is difficult to detect over the full life cycle with conventional non-destructive inspection. This creates an urgent demand for on-line, high-fidelity structural health monitoring (SHM) technology. Optical-fiber sensors—featuring minimal mass, micron-scale diameter, immunity to electromagnetic interference and the ability to be co-cured into composite laminates for distributed measurement—are widely regarded as the key enabling technology. This paper presents a comprehensive review of recent advances and engineering applications of optical fiber sensing. Emphasis is placed on its engineering applications covering wing strain mapping, landing-gear load tracking, fuselage deformation localization, and cure-process monitoring and low-velocity impact damage identification of composite materials. Emerging intelligent assessment methodologies are examined. Finally, the development trends of optical fiber sensing technology are prospected, offering a reference framework for future theoretical innovation and engineering deployment of aerospace composite SHM technology. Full article

Characterized by their atomic thickness and exceptional mechanical properties, two-dimensional (2D) materials offer a compelling platform for developing flexible optoelectronic devices that maintain performance stability under mechanical deformation such as bending and stretching. This review systematically summarizes and critically discusses the recent advancements in applying three prominent 2D material categories—graphene, transition metal dichalcogenides (TMDs, e.g., MoS₂ and WS₂), and MXenes—in flexible optoelectronics. We focus on their specific applications in flexible photodetectors, light-emitting devices, optical modulators, solar cells, and gas sensors. A particular emphasis is placed on analyzing the unique physicochemical properties of these materials and elucidating the underlying mechanisms that enable bandgap stability and efficient optoelectronic conversion under mechanical strain. The potential of these devices demonstrated here underscores their broad application prospects in wearable systems and self-powered electronic platforms. Finally, we conclude by discussing the challenges and future prospects in the field of flexible optoelectronic devices based on two-dimensional materials. Full article

This paper presents a methodology for monitoring the structural condition of remotely controlled demolition robots to prevent failures and extend service life. The approach integrates finite element method (FEM) simulations with strain gauge and vibroacoustic measurements. Iterative calibration of numerical models enabled accurate mapping of stress distribution, while optimal sensor placement improved monitoring precision. The study examined the impact of operational loads on durability and vibration resistance of critical components. The developed system enhances safety, operational efficiency, and structural reliability, providing a practical framework for predictive maintenance of demolition robots. Full article

Flexible strain sensors capable of conformal integration with living organisms are essential for advanced wearable electronics, human–machine interaction, and plant health. However, many existing sensors require complex fabrication or rely on non-breathable elastomer substrates that interfere with the physiological microenvironment of skin or plant tissues. Here, we present a low-cost, breathable, and highly stretchable strain sensor constructed from biomedical materials, in which a double-layer medical elastic bandage serves as the porous substrate and an intermediate conductive medical elastic tape impregnated with carbon nanotubes (CNTs) ink acts as the sensing layer. Owing to the hierarchical textile porosity and the deformable CNTs percolation network, the sensor achieves a wide strain range of 100%, a gauge factor of up to 2.72, and excellent nonlinear second-order fitting (R² = 0.997). The bandage substrate provides superior air permeability, allowing long-term attachment without obstructing moisture and gas exchange, which is particularly important for maintaining skin comfort and preventing disturbances to plant epidermal physiology. Demonstrations in human joint-motion monitoring and real-time plant growth detection highlight the device’s versatility and biological compatibility. This work offers a simple, low-cost yet effective alternative to sophisticated strain sensors designed for human monitoring and plant growth monitoring, providing a scalable route toward multifunctional wearable sensing platforms. Full article

Incorporating sensors such as microelectromechanical system (MEMS)-based inertial measurement units (IMUs) and strain gauges into aircraft structures has the potential to complement ground vibration testing results and improve the tracking of structural modes and wing shape in flight, as well as structural health monitoring. This study evaluates the feasibility and accuracy of employing MEMS accelerometers and gyroscopes together with strain gauges to estimate the structural modes of an aircraft. For this purpose, a ground vibration test was carried out on a 1:3 scaled Diana 2 glider model from which the displacement, rotation, and strain modes were estimated. The estimated modal parameters were compared with traditional piezoelectric accelerometer results and Finite Element Method model predictions. The results showed that the modal frequencies, damping ratios, and mode shapes estimated using MEMS IMUs and strain gauges closely matched the reference accelerometer estimates. Furthermore, the combination of displacement, rotation, and strain mode shapes allowed for greater insight into the structural dynamics. The exploratory use of gyroscopes for aircraft GVT allowed the structural torsion to be captured directly, thereby potentially simplifying future GVT setups by eliminating the need for placing accelerometers in pairs across the structure. Full article

Monitoring the curing process of concrete remains a challenging and critical aspect of modern construction, often hindered by labour-intensive, invasive, and inflexible methods. The primary aim of this study is to develop an integrated IoT-enabled platform for automated, real-time monitoring of concrete curing, using a combination of LoRa-based sensor networks and an LTE-M backhaul. The resulting ConMonity system employs embedded multi-sensor nodes—capable of measuring strain, temperature, and humidity–connected via an energy-efficient, TDMA-based LoRa wireless protocol to an LTE-M gateway with cloud-based management and analytics. By employing a robust architecture with battery-powered embedded nodes and adaptive firmware, ConMonity enables multi-modal, multi-site assessments and demonstrates stable, autonomous operation over multi-modal, multi-site assessment and demonstrates stable, autonomous operation over multi-month field deployments. Measured data are transmitted in a compact binary MQTT format, optimising cellular bandwidth and allowing secure, remote access via a dedicated mobile application. Operation in laboratory construction environments indicates that ConMonity outperforms conventional and earlier wireless monitoring systems in scalability and automation, delivering actionable real-time data and proactive alerts. The platform establishes a foundation for intelligent, scalable, and cost-effective monitoring of concrete curing, with future work focused on extending sensor modalities and enhancing resilience under diverse site conditions. Full article

This study investigates the correlation between strains obtained from the image-based technique GeoPIV and Fiber Bragg Grating (FBG) sensors’ measurements in Mechanically Stabilized Earth (MSE) systems, using scaled physical modeling in a geotechnical centrifuge. FBG sensors provide high-resolution, localized strain data along reinforcements, while GeoPIV offers full-field visualization of soil deformation. By calibrating GeoPIV outputs to microstrains, the complementary strengths of the two approaches are highlighted. In addition, the centrifuge setup reproduces realistic stress conditions, enhancing experimental reliability. The combined use of these methods not only improves understanding and monitoring of MSE behavior but also demonstrates strong potential for broader application in other laboratory-scale studies. Full article

This study investigates the effect of laser power, focal length, and number of passes on the fabrication of graphene-based strain sensors using a 450 nm diode laser at the upper limit of the UV spectrum. Polyimide substrates were irradiated to produce laser-induced graphene, and the resulting sensors were evaluated under three-point bending tests. The main requirements for deformation sensors—adequate conductivity, mechanical stability under bending, and high sensitivity (gauge factor)—were assessed through morphological analysis by SEM, Raman spectroscopy, and electrical characterization using the Van der Pauw method. The results indicate that laser power is the critical factor influencing graphene quality and sensor performance, while focal length has a negligible effect and additional passes reduce material quality and sensitivity. Overall, this work demonstrates the feasibility of producing functional, low-cost graphene strain sensors with a commercial diode laser, offering a scalable and affordable alternative for sensor fabrication. Full article

Distributed fiber-optic sensing (DFOS) with intentionally spaced mechanical fixity points was experimentally evaluated for the structural health monitoring (SHM) of reinforced concrete (RC) members. A full-scale four-point bending test was conducted on a 12 m RC beam (400 × 400 mm) instrumented with a single-mode DFOS cable incorporating internal anchors at 2 m intervals and bonded externally with structural epoxy. Brillouin time-domain analysis (BOTDA) provided distributed strain measurements at approximately 0.5 m spatial resolution, with all cables calibrated to ±15,000 µε. Under stepwise monotonic loading, the system captured smooth, repeatable strain baselines and clearly resolved localized tensile peaks associated with crack initiation and propagation. Long-gauge averages exhibited a near-linear load–strain response (R² ≈ 0.99) consistent with discrete foil and vibrating-wire strain gauges. Even after cracking, the DFOS signal remained continuous, while some discrete sensors showed saturation or scatter. Temperature compensation via a parallel fiber ensured thermally stable interpretation during load holds. The fixed-point configuration mitigated local debonding effects and yielded unbiased long-gauge strain data suitable for assessing serviceability and differential settlement. Overall, the results confirm the suitability of fixed-point DFOS as a durable, SHM-ready sensing approach for RC foundation elements and as a dense data source for emerging digital-twin frameworks. Full article

Regulatory agencies worldwide have implemented stringent measures to monitor and reduce Salmonella contamination in poultry products. Rapid quantitative detection methods enable producers to identify contamination early, implement corrective actions, and enhance food safety. This study aimed to develop and optimize a surface plasmon resonance (SPR) biosensor for the quantitative detection of Salmonella Typhimurium in ground chicken. The sensor surface was functionalized with a well-characterized monoclonal antibody specific to Salmonella flagellin, and an SPR workflow was established for quantitative analysis. Ground chicken samples were inoculated with four S. Typhimurium strains at contamination levels ranging from −0.5 to 3.5 Log CFU/g and enriched at 42 °C for 10 or 12 h prior to SPR analysis. Contamination levels were confirmed using the Most Probable Number (MPN) method. Linear regression analysis indicated that optimal quantification was achieved after 10 h of enrichment (R² ≥ 0.86), whereas extended enrichment (12 h) did not improve performance. The limit of quantification (LOQ) was below 1 CFU/g. A strong positive correlation (R² ≥ 0.85) was observed between SPR and MPN results, demonstrating consistency between the two methods. These findings highlight SPR as a rapid, reliable, and cost-effective alternative to conventional methods for Salmonella quantification. By delivering accurate results within a single day, SPR enhances testing efficiency and supports the production of safer poultry products, thereby reducing public health risks associated with Salmonella contamination. Full article

Distributed Acoustic Sensing (DAS) transforms conventional optical fibres into large-scale acoustic sensor arrays. While existing telecommunication cables are increasingly considered for DAS-based monitoring, their performance depends strongly on cable construction and strain transfer efficiency. In this study, the relative DAS signal amplitudes of three commercial telecommunication optical cables were experimentally compared using a benchtop Rayleigh backscattering-based interrogator under controlled laboratory conditions. By maintaining a constant temperature and ensuring no additional strain changes from the outside environment, we guaranteed that only strain-induced variations from acoustic excitations were measured. The results show clear differences in signal amplitude and signal-to-noise ratio (SNR) among the tested cables. The Microcable consistently produced the highest spatial peak amplitude (up to 0.029 a.u.) and SNR (up to 79), while the Duct cable reached 0.00268 a.u. with mean SNR ≈ 32. The Anti-Rodent cable showed low signal amplitude (0.0018 a.u.) but exhibited a high mean SNR (≈111) driven by an exceptional low noise floor in one of the runs. These findings reflect the variations in mechanical coupling between the fibre core and external perturbations and provide practical insights into the suitability of different telecom cable types for DAS applications, supporting informed choices for future deployments. Full article

The present work focuses on the inverse identification of loads acting on wing-like geometries, through strain measurements. These loads are considered quasi-static and considered acting at discrete stations across the span of the wing. A demonstrative case study is investigated, focusing on a complex composite structure, an Unmanned Aerial Vehicle (UAV) fin. To achieve this, a high-fidelity Finite Element model is developed, with “virtual” strain data generated through simulations. The technical challenge of optimal sensor placement is addressed with D-optimal designs, which promise sensor networks (sensor locations and strain components) that produce minimal uncertainty propagation from strain measurements to load estimates. These designs are obtained through the implementation of Genetic Algorithms. Different sensor networks with an increasing number of sensors are evaluated in order to identify a further reduction in epistemic uncertainty posed by the problem’s ill-conditioned nature. Full article

Humidity monitoring is essential in industrial and scientific scenarios, yet remains challenging for compact EMI (electromagnetic interference)-immune sensors with high sensitivity and robust stability. A novel fiber Bragg grating (FBG) humidity sensor was developed, which incorporated LiCl@UIO-66 microfillers within a poly(N-isopropylacrylamide) (PNIPAM) hydrogel matrix. Structural characterization using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and Fourier-transform infrared (FTIR) spectroscopy confirms that LiCl is confined or nanodispersed within intact UIO-66, and that interfacial ion–dipole/hydrogen-bonding exists between the composite and water. Systematic variation in coating time (30–720 min) reveals monotonic growth of the total wavelength shift with diminishing returns. A coating time of 4 h was found to yield a wavelength shift of approximately 0.38–0.40 nm, representing about 82% of the maximum shift observed at 12 h, while maintaining good quasi-linearity and favorable kinetics. Calibration demonstrates sensitivities of 6.7 pm/%RH for LiCl@UIO-66_33 and 10.6 pm/%RH for LiCl@UIO-66_51 over ~0–95%RH. Stepwise tests show response times t90 of ≈14 min for both composites, versus ≈30 min for UIO-66 and ≈55 min for neat PNIPAM. Long-term measurements on the 51 wt.% device are stable over the first ~20 days, with only slow drift thereafter, and repeated humidity cycling is reversible. The wavelength decreases monotonically during drying while settling time increases toward low RH. The synergy of hydrogel–MOF–salt underpins high sensitivity, accelerated transport, and practical stability, offering a scalable route to high-performance optical humidity sensing. Full article