Search Results (106)

This paper presents a high-sensitivity temperature and humidity synchronous measurement sensor based on virtual Vernier demodulation, designed to overcome the limitations of traditional sensors in high-sensitivity and synchronous measurements. By combining a dual-cavity parallel structure with the Virtual Vernier effect (VVE), two interferometers were designed, with one using a temperature-sensitive material (polydimethylsiloxane, PDMS) and the other using a humidity-sensitive material (polyvinyl alcohol, PVA) for temperature and humidity measurement, respectively. Based on actual interference spectra, a modulation function was used to generate the virtual reference interferometer spectrum, which was then superimposed with the sensing interferometer’s spectrum to form a virtual Vernier envelope. By monitoring the displacement of the envelope, precise measurements of temperature and humidity changes were achieved. Experimental results showed a temperature sensitivity of 5.61 nm/°C and 7.62 nm/°C, a humidity sensitivity of 0 nm/%RH and −3.07 nm/%RH, and average errors of 0.64% and 1.10% for temperature and humidity, respectively, demonstrating the feasibility of the method. The introduction of the virtual interferometer effectively reduces environmental interference with the measurement results and avoids the material loss and errors associated with traditional reference interferometers. More importantly, the VVE enables dynamic adjustment of the envelope magnification, thereby enhancing the sensor’s flexibility and overcoming the structural limitations of traditional interferometers. This sensor provides efficient and reliable technological support for future environmental monitoring and climate change research. Full article

Contact-force perception is a critical component of safe robotic grasping. With the rapid advances in embodied intelligence technology, humanoid robots have enhanced their multimodal perception capabilities. Conventional force sensors face limitations, such as complex spatial arrangements, installation challenges at multiple nodes, and potential interference with robotic flexibility. Consequently, these conventional sensors are unsuitable for biomimetic robot requirements in object perception, natural interaction, and agile movement. Therefore, this study proposes a sensorless external force detection method that integrates SuperPoint-Scale Invariant Feature Transform (SIFT) feature extraction with finite element analysis to address force perception challenges. A visual analysis method based on the SuperPoint-SIFT feature fusion algorithm was implemented to reconstruct a three-dimensional displacement field of the target object. Subsequently, the displacement field was mapped to the contact force distribution using finite element modeling. Experimental results demonstrate a mean force estimation error of 7.60% (isotropic) and 8.15% (anisotropic), with RMSE < 8%, validated by flexible pressure sensors. To enhance the model’s reliability, a dual-channel video comparison framework was developed. By analyzing the consistency of the deformation patterns and mechanical responses between the actual compression and finite element simulation video keyframes, the proposed approach provides a novel solution for real-time force perception in robotic interactions. The proposed solution is suitable for applications such as precision assembly and medical robotics, where sensorless force feedback is crucial. Full article

This study addresses the complex challenges associated with flexible mattress (soft mattress) installation in the sharply curved and deep-water sections of the Yangtze River, particularly in the Yaozui revetment reconstruction project. Under extreme hydrodynamic conditions—water depths exceeding 30 m and velocities over 2.5 m/s—the risk of structural failures such as displacement, flipping, or tearing of the mattress becomes significant. To improve construction safety and stability, the study integrates numerical modeling and on-site strain monitoring to analyze the mechanical response of flexible mattresses during deployment. A three-dimensional finite element model based on the catenary theory was developed to simulate stress distributions under varying flow velocities and angles, revealing stress concentrations at the mattress’s upper edge and reinforcement junctions. Concurrently, a real-time monitoring system using high-precision strain sensors was deployed on critical shipboard components, with collected data analyzed through a remote IoT platform. The results demonstrate strong correlations between mattress strain, flow velocity, and water depth, enabling the identification of high-risk operational thresholds. The proposed monitoring and early-warning framework offers a practical solution for managing construction risks in extreme riverine environments and contributes to the advancement of intelligent construction management for underwater revetment works. Full article

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

With the acceleration of industrialization, deformable mechanisms that can adapt to complex environments have gained widespread applications. Joints serve as carriers for transmitting forces and motions between components, and their stiffness significantly influences the static and dynamic characteristics of deformable mechanisms. A variable stiffness joint is crucial for ensuring the safety and reliability of the system, as well as for enhancing environmental adaptability. However, existing variable stiffness joints fail to meet the requirements for miniaturization, lightweight construction, and fast response. This paper proposes a piezoelectric-actuated variable stiffness miniature rotary joint featuring a compact structure, monitorable loading state, and rapid response. Given that the piezoelectric stack expands and contracts when energized, this paper proposes a transmission principle for stiffness adjustment by varying the pressure and friction between active and passive components. This joint utilizes a flexible hinge mechanism for displacement amplification and incorporates a torque sensor based on strain monitoring. A static model is developed based on piezoelectric equations and displacement amplification characteristics, and simulations confirm the feasibility of the stiffness adjustment scheme. The mechanical characteristics of various flexible hinge structures are analyzed, and the effects of piezoelectric actuation capability and external load on stiffness adjustment are examined. The experimental results demonstrate that the joint can adjust stiffness, and the sensor is calibrated using the least squares algorithm to monitor the stress state of the joint in real time. Full article

To meet the demand for submillimeter-level gripping capabilities in micro-grippers, an amplification mechanism based on a flexible four-bar linkage is proposed. The micro-gripper designed using this mechanism features a large gripping stroke in the millimeter range. First, the amplification effect of the flexible four-bar linkage was structurally designed and theoretically analyzed. Through kinematic analysis, a theoretical model was developed, demonstrating that the flexible four-bar linkage can achieve an extremely high amplification factor, thus providing a theoretical foundation for the design of the micro-gripper. Then, kinematic and mechanical simulations of the micro-gripper were conducted and validated using ANSYS 2025 simulation software, confirming the correctness of the theoretical analysis. Finally, an experimental platform was set up to analyze the characteristics of the micro-gripper, including its stroke, resolution, and gripping force. The results show that the displacement amplification factor of the gripper designed based on the flexible four-bar linkage can reach 40, with a displacement resolution of 50 nm and a gripping range of 0–880 μm. By using capacitive displacement sensors and strain sensors, integrated force and displacement control can be realized. The large-stroke micro-gripper based on the flexible four-bar linkage is compact, with a large stroke, and has broad application prospects. Full article

This study presents a self-powered smart wrist brace integrated with a piezoelectric sensor for real-time biomechanical monitoring during weightlifting activities. The system was designed to quantify wrist flexion across multiple loading conditions (0 kg, 0.5 kg, and 1.0 kg), leveraging mechanical strain-induced voltage generation to capture angular displacement. A flexible PVDF film was embedded within a custom-fitted wrist brace and tested on male and female participants performing controlled wrist flexion. The resulting voltage signals were analyzed to extract root-mean-square (RMS) outputs, calibration curves, and sensitivity metrics. To interpret the experimental results analytically, a lumped-parameter cantilever beam model was developed, linking wrist flexion angles to piezoelectric voltage output based on mechanical deformation theory. The model assumed a linear relationship between wrist angle and induced strain, enabling theoretical voltage prediction through simplified material and geometric parameters. Model-predicted voltage responses were compared with experimental measurements, demonstrating a good agreement and validating the mechanical-electrical coupling approach. Experimental results revealed consistent voltage increases with both wrist angle and applied load, and regression analysis demonstrated strong linear or mildly nonlinear fits with high $R^2$ values (up to 0.994) across all conditions. Furthermore, surface plots and strain sensitivity analyses highlighted the system’s responsiveness to simultaneous angular and loading changes. These findings validate the smart wrist brace as a reliable, low-power biomechanical monitoring tool, with promising applications in injury prevention, rehabilitation, and real-time athletic performance feedback. Full article

Tactile sensation across the whole hand, including the fingers and palm, is essential for manipulation and, therefore, is expected to be similarly useful for enabling dexterous robot manipulation. Tactile sensation would ideally be distributed (over large surface areas), have a high precision, and provide measurements in multiple axes, allowing for effective manipulation and interaction with objects of varying shapes, textures, friction, and compliance. Given the complex geometries and articulation of state-of-the-art robotic grippers and hands, they would benefit greatly from their surface being instrumented with a thin, curved, and/or flexible tactile sensor technology. However, the majority of current sensor technologies measure tactile information across a planar sensing surface or instrument-curved skin using relatively bulky camera-based approaches; proportionally in the literature, thin and flexible tactile sensor arrays are an under-explored topic. This paper, presents a thin, flexible, non-camera-based optical tactile sensor design as an investigation into the feasibility of adapting our novel LiVec sensing principle to curved and flexible surfaces. To implement the flexible sensor, flexible PCB technology is utilized in combination with other soft components. This proof-of-concept design eliminates rigid circuit boards, creating a sensor capable of providing localized 3D force and 3D displacement measurements across an array of sensing units in a small-thickness, non-camera-based optical tactile sensor skin covering a curved surface. The sensor consists of 16 sensing units arranged in a uniform 4 × 4 grid with an overall size of 30 mm × 30 mm × 7.2 mm in length, width, and depth, respectively. The sensor successfully estimated local XYZ forces and displacements in a curved configuration across all sixteen sensing units, the average force bias values ($\overline{\mu }$) were −1.04 mN, −0.32 mN, and −1.31 mN, and the average precision ($\overline{SD}$) was 54.49 mN, 55.16 mN and 97.15 mN, for the X, Y, Z axes, respectively, the average displacement bias values ($\overline{\mu }$) were 1.58 μm, 0.29 μm, and −1.99 μm, and the average precision values ($\overline{SD}$) were 221.61 μm, 247.74 μm, and 44.93 μm for the X, Y, and Z axes, respectively. This work provides crucial insights into the design and calibration of future curved LiVec sensors for robotic fingers and palms, making it highly suitable for enhancing dexterous robotic manipulation in complex, real-world environments. Full article

In aerospace and new-energy vehicle manufacturing, there is an increasing demand for the high-quality joining of large, curved aluminum alloy structures. This study presents a robotic friction stir welding (RFSW) system employing a force/position hybrid control. An eight-axis linkage platform integrates an electric spindle, multidimensional force sensors, and a laser displacement sensor, ensuring trajectory coordination between the robot and the positioner. By combining long-range constant displacement with small-range constant pressure—supplemented by an adaptive transition algorithm—the system regulates the axial stirring depth and downward force. The experimental results confirm that this approach effectively compensates for robotic flexibility, keeping weld depth and pressure deviations within 5%, significantly improving seam quality. Further welding verification was performed on typical curved panels for aerospace applications, and the results demonstrated strong adaptability under high-load, multi-DOF conditions, without crack formation. This research could advance the field toward more robust, automated, and adaptive RFSW solutions for aerospace, automotive, and other high-end manufacturing applications. Full article

The development of intelligent tire technology has attracted increasing attention from researchers to build different tire models to obtain the state parameters of the tire and to try to correlate these parameters with sensors. To address the challenge of characterizing the evolution of wear in traditional tire mechanics models, this study proposes a physical model that incorporates tire wear. The model is an improvement over the traditional flexible ring model, incorporating brush theory. By establishing the mechanical equilibrium equation of the tread unit, a tire dynamic equation incorporating wear state variables is constructed. The strain–displacement relationship is analyzed to determine the correlation between the strain field and the displacement field. The results show that the strain signals obtained from the physical model and the finite element model maintain a high degree of consistency, validating the reliability and effectiveness of the proposed model. In addition, the correlation between the tire wear and strain signal characteristics was successfully revealed by comparing the physical model and the finite element model. The proposed model provides a theoretical foundation for future research on intelligent tires, as well as a basis for related studies on tire wear, tire lifespan, and tire mechanical properties. Full article

Chatter commonly emerges during milling procedures, resulting in an array of problems such as defective workpiece surface and diminished machining efficiency. To control chatter, an active electromagnetic tool holder system is proposed, including the active structure with an electromagnetic actuator installed at the tool holder position and a time-delay output feedback chatter control method for low immersion milling. More specifically, a noncontact two-degree-of-freedom active magnetic bearing (AMB) actuator is developed and integrated with displacement sensors at the tool holder position, making the actuator and sensors closer to the cutting point. Under low immersion milling conditions, both the thin-walled workpieces and tool flexibility are considered in the controller design, as well as practical physical limitations including the bandwidth of the power amplifier and the output current constraints of the actuator. Numerical simulation and experiments under low immersion milling conditions are carried out. The results demonstrate that the proposed active electromagnetic tool holder system exhibits good control consequences on the chatter of thin-walled workpieces and tools under low immersion milling. Full article

Monitoring of immune factors, including interferon-gamma (IFN-γ), holds great importance for understanding immune responses and disease diagnosis. Wearable sensors enable continuous and non-invasive detection of immune markers in sweat, drawing significant attention to their potential in real-time health monitoring and personalized medicine. Among these, electrochemical sensors are particularly advantageous, due to their excellent signal responsiveness, cost-effectiveness, miniaturization, and broad applicability, making them ideal for constructing wearable sweat sensors. In this study, we present a flexible and sensitive wearable platform for the detection of IFN-γ, utilizing a DNA hydrogel with favorable loading performance and sample collection capability, and the application of mobile software achieves immediate data analysis and processing. This platform integrates three-dimensional DNA hydrogel functionalized with IFN-γ-specific aptamers for precise target recognition and efficient sweat collection. Signal amplification is achieved through target-triggered catalytic hairpin assembly (CHA), with DNA hairpins remarkably enhancing sensitivity. Ferrocene-labeled reporting strands immobilized on a screen-printed carbon electrode are displayed via CHA-mediated strand displacement, leading to a measurable reduction in electrical signals. These changes are transmitted to a custom-developed mobile application via a portable electrochemical workstation for real-time data analysis and recording. This wearable sensor platform combines the specificity of DNA aptamers, advanced signal amplification, and the convenience of mobile data processing. It offers a high-sensitivity approach to detecting low-abundance targets in sweat, paving the way for new applications in point-of-care diagnostics and wearable health monitoring. Full article

Direct wide-bandgap III-Ns and II-Os have recently gained considerable attention due to their unique electrical and chemical properties. These novel semiconductors are being explored to design short-wavelength light-emitting diodes, sensors/biosensors, photodetectors for integration into flexible transparent nanoelectronics/photonics to achieve high-power radio-frequency modules, and heat-resistant optical switches for communication networks. Knowledge of the elastic constants structural and mechanical properties has played crucial roles both in the basic understanding and assessing materials’ use in thermal management applications. In the absence of experimental structural, elastic constants, and mechanical traits, many theoretical simulations have yielded inconsistent results. This work aims to investigate the basic characteristics of tetrahedrally coordinated, partially ionic BeO, MgO, ZnO, and CdO, and partially covalent BN, AlN, GaN, and InN materials. By incorporating a bond-orbital and a valance force field model, we have reported comparative results of our systematic calculations for the bond length $\mathrm{d}$, bond polarity ${\mathsf{\alpha }}_{\mathrm{P}}$, covalency ${\mathsf{\alpha }}_{\mathrm{C}}$, bulk modulus $\mathrm{B}$, elastic stiffness $\mathrm{C}(={\displaystyle \frac{\left[{\mathrm{c}}_{11}-{\mathrm{c}}_{12}\right]}{2}})$, bond-stretching $\mathsf{\alpha }$ and bond-bending $\mathsf{\beta }$ force constants, Kleinmann’s internal displacement ζ, and Born’s transverse effective charge ${\mathrm{e}}_{\mathrm{T}}^{*}$. Correlations between $\mathrm{C}/\mathrm{B}$, $\mathsf{\beta }$/$\mathsf{\alpha }$, ${\displaystyle \frac{{\mathrm{c}}_{12}}{{\mathrm{c}}_{11}}},$ ζ, $\mathrm{a}\mathrm{n}\mathrm{d}$ ${\mathsf{\alpha }}_{\mathrm{C}}$revealed valuable trends of structural, elastic, and bonding characteristics. The study noticed AlN and GaN (MgO and ZnO) showing nearly comparable features, while BN (BeO) is much harder compared to InN (CdO) material, with drastically softer bonding. Calculations of microhardness $\mathrm{H}$, shear modulus $\mathrm{G},$ and Young’s modulus $\mathrm{Y}$ have predicted BN (BeO) satisfying a criterion of super hardness. III-Ns (II-Os) could be vital in electronics, aerospace, defense, nuclear reactors, and automotive industries, providing integrity and performance at high temperature in high-power applications, ranging from heat sinks to electronic substrates to insulators in high-power devices. Full article

Optical Fiber Displacement Sensors (OFDSs) provide several advantages over conventional sensors, including their compact size, flexibility, and immunity to electromagnetic interference. These features make OFDSs ideal for use in confined spaces, such as turbines, where direct laser access is impossible. A critical aspect of OFDS performance is the geometry of the fiber bundle, which influences key parameters such as sensitivity, range, and dead zones. In this work, we present a streamlined design methodology for azimuthally symmetric OFDSs to improve the linear range of these sensors. The most effective configuration we propose is the pentafurcated bundle, which consists of a central transmitting fiber surrounded by four concentric rings of fibers with different radii. Our experimental results show that the pentafurcated designs increase both the range—up to 10.5 mm—and the sensitivity of the sensor—$2{\mathrm{mm}}^{-1}$—while minimizing the dead zone of the sensor (2.5 mm), allowing accurate measurements even at very short distances Full article