Search Results (758)

Soil compaction is a pivotal factor influencing crop growth and yield, and its accurate assessment is imperative for precision agricultural management. Soil mechanical resistance is the key indicator of soil compaction, with accurate measurement enabling precise assessment. Dynamic soil mechanical resistance measurement outperforms conventional manual fixed-point sampling in data acquisition efficiency. In this paper, a methodology is proposed for the dynamic acquisition of soil mechanical resistance using a flexible thin-film pressure sensor. This study dynamically captures soil mechanical resistance at three depths (5 cm, 10 cm, and 15 cm) under dynamic machinery operating conditions. A device was designed for the detection of soil mechanical resistance, and a prediction model for soil mechanical resistance was developed based on the Kalman filter algorithm. Tests were conducted under steady-state and variable-load conditions, and the predicted values accurately tracked the reference pressure. Soil tank trials showed that at an operating speed of 0.69–0.72 km/h, the average prediction errors for the three soil layers were 2.03%, 1.48%, and 6.27%, with the coefficient of determination (R²) between predicted and measured values reaching 0.96. The system effectively predicts multi-depth soil resistance, providing novel theoretical and technical approaches for dynamic acquisition. Full article

Miniaturized pressure sensors fabricated via micro-electro-mechanical systems (MEMSs) technology are ubiquitous in modern applications. However, the massively produced MEMS pressure sensors, prior to being practically used, need to be calibrated one by one to eliminate or minimize nonlinearity and zero drift. This paper presents a systematic design for the testing and calibration process of MEMS-based absolute pressure sensors. Firstly, a numerical analysis is carried out using finite element method (FEM) simulation, which verifies the accuracy of the temperature control of the physical calibration system. The simulation results reveal a slight non-uniformity of temperature distribution, which is then taken into consideration in the calibration algorithm. Secondly, deploying a home-made calibration system, the MEMS pressure sensors are tested automatically and rapidly. The experimental results show that each batch, which consists of nine sensors, can be calibrated in 80 min. The linearity and temperature coefficient (TC) of the pressure sensors are reduced from 46.5% full-scale (FS) and −1.35 × 10⁻⁴ V·K⁻¹ to 1.5% FS and −8.8 × 10⁻⁷ V·K⁻¹. Full article

The treatment of chronic wounds and pressure sores is an important challenge in the context of public health and the effectiveness of patient treatment. Therefore, new methods are being developed to reduce or, in extreme cases, to initiate and conduct the wound healing process. This article presents an innovative smart bandage, programmable using a smartphone, which generates small amplitude impulse vibrations. The communication between the smart bandage and the smartphone is realized using BLE. The possibility of programming the smart bandage allows for personalized therapy. Owing to the built-in MEMS sensor, the smart bandage makes it possible to monitor work during rehabilitation and implement an auto-calibration procedure. The flexible, openwork mechanical structure of the dressing was made in 3D printing technology, thanks to which the solution is easy to implement and can be used together with traditional dressings to create hybrid ones. Miniature electronic circuits and actuators controlled by the PWM signal were designed as replaceable elements; thus, the openwork structure can be treated as single-use. The smart bandage containing six actuators presented in this article generates oscillations in the range from about 40 Hz to 190 Hz. The system generates low-amplitude vibrations, below 1 g. The actuators were operated at a voltage of 1.65 V to reduce energy consumption. For comparison, the actuators were also operated at the nominal voltage of 3.17 V, as specified by the manufacturer. Full article

Flexible hydrogel sensors demonstrate emerging applications, such as wearable electronics, soft robots, and humidity smart devices, but their further application is limited due to their single-responsive behavior and unstable, low-sensitivity signal output. This study develops a dual-responsive starch-based conductive hydrogel via a facile “one-pot” strategy, achieving mechanically robust pressure sensing and ultra-sensitive humidity detection. The starch-Poly (2,3-dihydrothieno-1,4-dioxin)-poly (styrenesulfonate) (PEDOT:PSS)-glutaraldehyde (SPG) hydrogel integrates physical entanglement and covalent crosslinking to form a porous dual-network architecture, exhibiting high compressive fracture stress (266 kPa), and stable electromechanical sensitivity (ΔI/I₀, ~2.3) with rapid response (0.1 s). In its dried state (D-SPG), the film leverages the starch’s hygroscopicity for humidity sensing, detecting minute moisture changes (ΔRH = 6.6%) within 120 ms and outputting 0.4~0.5 (ΔI/I₀) signal amplitudes. The distinct state-dependent responsiveness enables tailored applications: SPG monitors physiological motions (e.g., pulse waves and joint movements) via conformal skin attachment, while D-SPG integrated into masks quantifies respiratory intensity with 3× signal enhancement during exercise. This work pioneers a sustainable candidate for biodegradable flexible electronics, overcoming trade-off limitations between mechanical integrity, signal stability, and dual responsiveness in starch hydrogels through synergistic network design. Full article

The geometric symmetry of the pipeline constitutes a critical determinant in regulating the energy propagation dynamics during the explosion process. In the present study, a transparent plexiglass pipe experimental system incorporating a range of angles (30° to 150°) was meticulously constructed. Leveraging high-frequency pressure sensors in conjunction with high-speed camera technology, this investigation examines the influence of the pipe angle, which disrupts geometric symmetry, on the coupling explosion of gas and coal dust. The experimental findings illustrate that an increase in the pipeline turning angle significantly enhances the velocity of the explosion flame front (with the maximum velocity escalating from 97.92 m/s to 361.28 m/s) and concurrently reduces the total propagation time (from 71 ms to 56.5 ms). Moreover, there is a notable reduction in the duration of the explosion flame, decreasing from 240.5 ms to 64.17 ms at the coal dust deposition point. The peak overpressure of the shock wave exhibits a significant increase with the augmentation of the turning angle (rising from 7.07 kPa at 30° to 88.40 kPa at 150°). Furthermore, the overpressure in the fore section of the turning is amplified, attributable to the superimposition of reflected waves and turbulent effects. This study elucidates critical mechanisms including turbulence-enhanced combustion, secondary dust generation from coal dust, and energy dissipation resulting from abrupt alterations in pipeline geometry, thereby offering a theoretical framework for the prevention and effective emergency management of coal mine explosion disasters. Full article

The increasing depth of coal mine construction has led to complex geological conditions involving high ground stress and elevated groundwater levels, presenting new challenges for water-sealing technologies in rock microfissure grouting. This study investigates ultrafine cement grouting in microfissures through systematic analysis of slurry properties and grouting simulations. Through systematic analysis of ultrafine cement grout performance across water–cement (W/C) ratios, this study establishes optimal injectable mix proportions. Through dedicated molds, sandstone-like microfissures with 0.2 mm apertures and controlled roughness (JRC = 0–2, 4–6, 10–12) were fabricated, and instrumented with fiber Bragg grating (FBG) sensors for real-time strain monitoring. Triaxial stress-permeation experiments under 6 and 7 MPa confining pressures quantify the coupled effects of fissure roughness, grouting pressure, and confining stress on volumetric flow rate and fissure deformation. Key findings include: (1) Slurry viscosity decreased monotonically with higher W/C ratios, while bleeding rate exhibited a proportional increase. At a W/C ratio = 1.6, the 2 h bleeding rate reached 7.8%, categorizing the slurry as unstable. (2) Experimental results demonstrate that increased surface roughness significantly enhances particle deposition–aggregation phenomena at grouting inlets, thereby reducing the success rate of grouting simulations. (3) The volumetric flow rate of ultrafine cement grout decreases with elevated roughness but increases proportionally with applied grouting pressure. (4) Under identical grouting pressure conditions, the relative variation in strain values among measurement points becomes more pronounced with increasing roughness of the specimen’s microfissures. This research resolves critical challenges in material selection, injectability, and seepage–deformation mechanisms for microfissure grouting, establishing that the W/C ratio governs grout performance while surface roughness dictates grouting efficacy. These findings provide theoretical guidance for water-blocking grouting engineering in microfissures. Full article

Hydrogels exhibit significant promise for advanced flexible sensing applications owing to their intrinsic softness, biocompatibility, and customizable functionalities. Nevertheless, their limited mechanical strength poses a critical barrier to practical implementation. In this study, we engineered a mechanically robust alginate/chitosan (SA/CS) hydrogel reinforced with meta-aramid (PMIA) nanofibers. The resulting composite hydrogel achieves a tensile strength of 16.8 MPa, substantially exceeding the performance of conventional biomass-derived hydrogels. When employed as a flexible sensor, the hydrogel demonstrates exceptional pressure-sensing capabilities, featuring high sensitivity (178.41 MΩ/MPa below 5 kPa), rapid response kinetics (0.4–0.8 s), and sustained stability (>200 cycles). Leveraging these properties, we successfully monitored vocal cord vibrations and finger motion trajectories, highlighting their potential for biomechanical sensing applications. Full article

This systematic review critically examines the benefits and challenges of high-compression-ratio (CR) implementation in hybrid-dedicated engines, recognizing CR increase as a pivotal strategy for enhancing the indicated thermal efficiency to achieve carbon peak and carbon neutrality goals. However, excessively high CRs face critical constraints, including intensified knock propensity, increased heat transfer (HTR) losses, reduced combustion stability, augmented dissociation losses, and cold-start misfire risks. The feasibility and necessity of CR enhancement in hybrid systems were comprehensively evaluated based on these factors, with fundamental mechanisms of the detrimental effects elucidated. To address these challenges, optimized countermeasures were synthesized: knock suppression via high-octane fuels, EGR technology, lean combustion, and in-cylinder water injection; heat transfer reduction through thermal barrier coatings and independent CR/expansion-ratio control; misfire risk monitoring using ion current or cylinder pressure sensors. These approaches provide viable pathways to overcome high-CR limitations and optimize engine performance. Nevertheless, current research remains confined to isolated solutions, warranting future focus on integrated optimization mechanisms investigating synergistic interactions of multiple strategies under high-CR conditions. Full article

Variable-thrust liquid rocket engines are essential for precision landing in deep-space exploration, reusable launch vehicle recovery, high-accuracy orbital maneuvers, and emergency obstacle evasions of space drones. However, with the increasingly complex space missions, challenges remain with the development of different technical schemes. In view of these issues, this paper systematically reviews the technology’s evolution through mechanical throttling, electromechanical precision regulation, and commercial space-driven deep throttling. Then, the development of key variable thrust technologies for liquid rocket engines is summarized from the perspective of thrust regulation and control strategy. For instance, thrust regulation requires synergistic flow control devices and adjustable pintle injectors to dynamically match flow rates with injection pressure drops, ensuring combustion stability across wide thrust ranges—particularly under extreme conditions during space drones’ high-maneuver orbital adjustments—though pintle injector optimization for such scenarios remains challenging. System control must address strong multivariable coupling, response delays, and high-disturbance environments, as well as bottlenecks in sensor reliability and nonlinear modeling. Furthermore, prospects are made in response to the research progress, and breakthroughs are required in cryogenic wide-range flow regulation for liquid oxygen-methane propellants, combustion stability during deep throttling, and AI-based intelligent control to support space drones’ autonomous orbital transfer, rapid reusability, and on-demand trajectory correction in complex deep-space missions. Full article

Wearable pressure sensors have emerged as vital tools in personalized monitoring, promising transformative advances in patient care and diagnostics. Nevertheless, conventional devices frequently suffer from limited sensitivity, inadequate flexibility, and concerns regarding biocompatibility. Herein, we introduce silk fibroin, a naturally occurring protein extracted from silkworm cocoons, as a promising material platform for next-generation wearable sensors. Owing to its remarkable biocompatibility, mechanical robustness, and structural tunability, silk fibroin serves as an ideal substrate for constructing capacitive pressure sensors tailored to medical applications. We engineered silk-derived capacitive architecture and evaluated its performance in real-time human motion and physiological signal detection. The resulting sensor exhibits a high sensitivity of 18.68 kPa⁻¹ over a broad operational range of 0 to 2.4 kPa, enabling accurate tracking of subtle pressures associated with pulse, respiration, and joint articulation. Under extreme loading conditions, our silk fibroin sensor demonstrated superior stability and accuracy compared to a commercial resistive counterpart (FlexiForce™ A401). These findings establish silk fibroin as a versatile, practical candidate for wearable pressure sensing and pave the way for advanced biocompatible devices in healthcare monitoring. Full article

Microfluidic platforms offer a powerful approach for ultimately replicating vascularization in vitro, enabling precise microscale control and manipulation of physical parameters. Despite these advances, the real-time ability to monitor and quantify mechanical forces—particularly pressure—within microfluidic environments remains constrained by limitations in cost and compatibility across diverse device architectures. Our work presents an advanced experimental module for quantifying pressure within a vascularizing microfluidic platform. Equipped with an integrated Arduino microcontroller and image monitoring, the system facilitates real-time remote monitoring to access temporal pressure and flow dynamics within the device. This setup provides actionable insights into the hemodynamic parameters driving vascularization in vitro. In-line pressure sensors, interfaced through I2C communication, are employed to precisely record inlet and outlet pressures during critical stages of microvasculature tubulogenesis. Flow measurements are obtained by analyzing changes in reservoir volume over time (dV/dt), correlated with the change in pressure over time (dP/dt). This quantitative assessment of various pressure conditions in a microfluidic platform offers insights into their impact on microvasculature perfusion kinetics. Data acquisition can help inform and finetune functional vessel network formation and potentially enhance the durability, stability, and reproducibility of engineered in vitro platforms for organoid vascularization in regenerative medicine. Full article

By embedding optical fiber sensors into fiber preforms and utilizing liquid molding processes such as resin transfer molding (RTM), intelligent composite materials with self-sensing capabilities can be fabricated. In the liquid molding process of these intelligent composites, the quality of the final product is highly dependent on the resin flow and impregnation effects. The embedding of optical fibers can affect the microscopic flow and impregnation behavior of the resin; therefore, it is necessary to investigate the specific impact of optical fiber embedding on the resin flow and impregnation of fiber bundles. Due to the difficulty of directly observing this process at the microscopic scale through experiments, numerical simulation has become a key method for studying this issue. This paper focuses on the resin micro-flow in RTM processes for intelligent composites with embedded optical fibers. Firstly, a steady-state analysis of the resin flow and impregnation process was conducted using COMSOL 6.0 obtaining the velocity and pressure field distribution characteristics under different optical fiber embedding conditions. Secondly, the dynamic process of resin flow and impregnation of fiber bundles at the microscopic scale was simulated using Fluent 2022R2. This study comprehensively analyzes the impact of different optical fiber embedding configurations on resin flow and impregnation characteristics, determining the impregnation time and porosity after impregnation under different optical fiber embedding scenarios. Additionally, this study reveals the mechanisms of pore formation and their distribution patterns. The research findings provide important theoretical guidance for optimizing the RTM molding process parameters for intelligent composite materials. Full article

In this study, we present a flexible piezoelectric nanogenerator based on a zinc oxide (ZnO)/polyvinylidene fluoride (PVDF) nanocomposite electrospun onto a hemisphere-patterned PDMS substrate. The nanogenerator was fabricated by replicating a silicon mold with inverted hemispheres into PDMS, followed by direct electrospinning of ZnO-dispersed PVDF nanofibers. Varying the ZnO concentration from 0.6 to 1.4 wt% allowed us to evaluate its effect on structural, dielectric, and piezoelectric properties. The nanogenerator containing 0.8 wt% ZnO exhibited the thinnest fibers (371 nm), the highest β-phase fraction (85.6%), and the highest dielectric constant (35.8). As a result, it achieved the maximum output voltage of 7.30 V, with excellent signal consistency under an applied pressure of 5 N. Comparisons with pristine PVDF- and ZnO/PVDF-only devices demonstrated the synergistic effect of ZnO loading and patterned PDMS on the enhancement of piezoelectric output. The hemisphere-patterned PDMS substrate improved the mechanical strain distribution, interfacial contact, and charge collection efficiency. These results highlight the potential of ZnO/PVDF/PDMS hybrid nanogenerators for use in wearable electronics and self-powered sensor systems. Full article

In this research, a single composite-type stretchable triboelectric nanogenerator (TENG) is proposed for efficient energy harvesting and handwriting recognition. The composite TENGs were fabricated by blending dielectric barium titanate (BT) and conductive carbon nanotubes (CNTs) in varying amounts into a styrene–butadiene rubber matrix. The energy harvesting efficiency depends on the type and amount of fillers, as well as their dispersion within the matrix. Stearic acid modification of BT enables near-nanoscale filler distribution, resulting in high energy conversion efficiencies. The composite achieved power efficiency, power density, charge efficiency, and charge density values of 1.127 nW/N, 8.258 mW/m³, 0.146 nC/N, and 1.072 mC/m³, respectively, under only 2% cyclic compressive strain at 0.85 Hz. The material performs better at low stress–strain ranges, exhibiting higher charge efficiency. The generated charge in the TENG composite is well correlated with the compressive stress, which provides a minimum activation pressure of 0.144 kPa, making it suitable for low-pressure sensing applications. A flat composite with dimensions of 0.02 × 6 × 5 cm³ can produce a power density of 26.04 W/m³, a charge density of 0.205 mC/m³, and an output voltage of 10 V from a single hand pat. The rubber composite also demonstrates high accuracy in handwriting recognition across different individuals, with clear differences in sensitivity curves. Repeated attempts by the same person show minimal deviation (<5%) in writing time. Additionally, the presence of reinforcing fillers enhances mechanical strength and durability, making the composite suitable for long-term cyclic energy harvesting and wearable sensor applications. Full article

In the context of increasing the complexity and intelligence of modern power systems, traditional maintenance approaches for circuit breakers have shown limitations in meeting both reliability and economic requirements. This paper proposes a multi-sensor data fusion fault detection method based on the RF-Adaboost algorithm for spring-operated circuit breakers. By integrating pressure, speed, coil current, and energy storage motor sensors into the mechanism, multi-source operational data are acquired and processed via denoising and feature extraction techniques. A fault detection model is then constructed using the RF-Adaboost classifier. The experimental results demonstrate that the proposed method achieves over 96% accuracy in identifying typical fault states such as coil voltage deviation, reset spring fatigue, and closing spring degradation, outperforming conventional approaches. These results validate the model’s effectiveness and robustness in diagnosing complex mechanical failures in circuit breakers. Full article