Search Results (1,598)

In order to correctly measure the shock wave pressure generated by a near-field explosion, and while considering the limitations of the measurement and calibration method of the current bar pressure sensor, an improved shock wave pressure measurement method was designed based on a bar pressure sensor combined with photon Doppler velocimetry (PDV) and strain measurement. By measuring the strain on the pressure bar and the particle velocity on the rear-end face, the shock wave pressure applied on the front-end face of the pressure bar was calculated based on one-dimensional stress wave theory. On the other hand, a calibration method was designed to validate the reliability of the test system. Based on the split-Hopkinson pressure bar (SHPB) loading experiment, the transmission characteristics of stress wave in the bar and the accuracy of the system test results were verified. The results indicated that the stress wave measurement results were consistent with the one-dimensional elementary theoretical calculation results of stress wave propagation in different wave-impedance materials, and the peak deviation measured by PDV and strain measurement method was less than 1.5%, which proved the accuracy of the test method and the feasibility of the calibration method. Full article

Wearable sensors are central to health-monitoring systems, but the limited capacity of compact batteries poses a challenge for long-term and maintenance-free operation. In this study, we investigated ambient electromagnetic wave (AEMW) energy harvesting using a human body antenna (HBA) as a means to supply power to wearable sensors. The power density and frequency distribution of AEMWs were measured in diverse indoor, outdoor, and basement environments. We designed and fabricated a flexible HBA–circuit interface electrode, optimized for broadband impedance matching when worn on the body. Experimental comparisons using a simulated AEMW source demonstrated that the HBA outperformed a conventional small whip antenna, particularly at frequencies below 300 MHz. Furthermore, the outdoor measurements indicated that the power harvested by the HBA was estimated to be −31.9 dBm (0.64 μW), which is sufficient for the intermittent operation of low-power wearable sensors and Bluetooth Low Energy modules. The electromagnetic safety was also evaluated through numerical analysis, and the specific absorption rate was confirmed to be well below the international safety limits. These findings indicate that HBA-based AEMW energy harvesting provides a practical and promising approach to achieving battery-maintenance-free wearable devices. Full article

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

This work presents an innovative hydrothermal approach for fabricating flexible piezoelectric PZT thin films on 20 μm titanium foil substrates using TiO₂ and SrTiO₃ (STO) interlayers. Three heterostructures (Ti/PZT, Ti/TiO₂/PZT, and Ti/TiO₂/STO/PZT) were synthesized to enable low-temperature growth and improve ferroelectric performance for advanced flexible MEMS. Characterizations including XRD, PFM, and P–E loop analysis evaluated crystallinity, piezoelectric coefficient d₃₃, and polarization behavior. The results demonstrate that the multilayered Ti/TiO₂/STO/PZT structure significantly enhances performance. XRD confirmed the STO buffer layer effectively reduces lattice mismatch with PZT to ~0.76%, promoting stable morphotropic phase boundary (MPB) composition formation. This optimized film exhibited superior piezoelectric and ferroelectric properties, with a high d₃₃ of 113.42 pm/V, representing an ~8.65% increase over unbuffered Ti/PZT samples, and displayed more uniform domain behavior in PFM imaging. Impedance spectroscopy showed the lowest minimum impedance of 8.96 Ω at 10.19 MHz, indicating strong electromechanical coupling. Furthermore, I–V measurements demonstrated significantly suppressed leakage currents in the STO-buffered samples, with current levels ranging from 10⁻¹² A to 10⁻⁹ A over ±3 V. This structure also showed excellent fatigue endurance through one million electrical cycles, confirming its mechanical and electrical stability. These findings highlight the potential of this hydrothermally engineered flexible heterostructure for high-performance actuators and sensors in advanced MEMS applications. Full article

The use of aerial robots for inspection and maintenance in industrial settings demands high maneuverability, precise control, and reliable measurements. This study explores the development of a fully customized unmanned aerial manipulator (UAM), composed of a tilting drone and an articulated robotic arm, designed to perform non-destructive in-contact inspections of iron structures. The system is intended to operate in complex and potentially hazardous environments, where autonomous execution is supported by shared-control strategies that include human supervision. A parallel force–impedance control framework is implemented to enable smooth and repeatable contact between a sensor for ultrasonic testing (UT) and the inspected surface. During interaction, the arm applies a controlled push to create a vacuum seal, allowing accurate thickness measurements. The control strategy is validated through repeated trials in both indoor and outdoor scenarios, demonstrating consistency and robustness. The paper also addresses the mechanical and control integration of the complex robotic system, highlighting the challenges and solutions in achieving a responsive and reliable aerial platform. The combination of semi-autonomous control and human-in-the-loop operation significantly improves the effectiveness of inspection tasks in hard-to-reach environments, enhancing both human safety and task performance. Full article

This paper proposes an adaptive human–robot concurrent control scheme that achieves the appropriate gait trajectory for a robotic leg prosthesis to improve the wearer’s comfort in various tasks. To accommodate different wearers, a neuromuscular-force-based impedance method was developed using muscle activation to reshape gait trajectory. To eliminate the use of sensors for torque measurement, a disturbance observer was established to estimate the interaction force between the human residual limb and the prosthetic receptacle. The cost function was combined with the interaction force and tracking errors of the joints. We aim to reduce the cost function by minimally changing the control weight of the gait trajectory generated by the Central Pattern Generator (CPG). The control scheme was primarily based on human-in-the-loop optimization to search for a suitable control weight to regenerate the appropriate gait trajectory. To handle the uncertainties and unknown coupling of the motors, an adaptive law was designed to estimate the unknown parameters of the system. Through a stability analysis, the control framework was verified by semi-globally uniformly ultimately bounded stability. Experimental results are discussed, and the effectiveness of the adaptive control framework is demonstrated. In Case 1, the mean error (MEAN) of the tracking performance was $3.6°$ and $3.3°$, respectively. And the minimized mean square errors (MSEs) of the tracking performance were $2.3°$ and $2.8°$, respectively. In Case 2, the mean error (MEAN) of the tracking performance is $2.7°$ and $3.1°$, respectively. And the minimized mean square errors (MSEs) of the tracking performance are $1.8°$ and $2.4°$, respectively. In Case 3, the mean errors (MEANs) of the tracking performance for subject1 and 2 are $2.4°$, $2.9°$, $3.4°$, and $2.2°$, $2.8°$, $3.1°$, respectively. The minimized mean square errors (MSEs) of the tracking performance for subject1 and 2 were $1.6°$, $2.3°$, $2.6°$, and $1.3°$, $1.7°$, $2.2°$, respectively. Full article

This paper presents the electrical characterization of a flexible supercapacitor with a unique architecture incorporating a piezoelectric PVDF-TrFE film sandwiched between PEDOT:PSS:Graphene and LiTaO₃ as a charge-generating and charge-transferring layer. Impedance spectroscopy measurements reveal frequency-dependent capacitance behavior, reflecting the contributions of both piezoelectric and supercapacitor capacitances. Charge–discharge cycling tests demonstrate the device’s energy storage capabilities and indicate a potential enhancement through the piezoelectric effect. Supercapacitor cycling tests demonstrate the device’s energy storage capabilities, with an estimated specific capacitance of 10.14 F/g, a power density of 16.3 W/g, an energy density of 5.63 Wh/kg, and a Coulombic efficiency of 96.1% from an active area of 1 cm². The proposed structure can serve as an independent harvester and storage for low-power, wearable sensors. Full article

In recent decades, flexible electronics have witnessed remarkable advancements in multiple fields, encompassing wearable electronics, human–machine interfaces (HMI), clinical diagnosis, and treatment, etc. Nevertheless, conventional rigid electronic devices are fundamentally constrained by their inherent non-stretchability and poor conformability, limitations that substantially impede their practical applications. In contrast, conductive hydrogels (CHs) for electronic skin (E-skin) and healthcare monitoring have attracted substantial interest owing to outstanding features, including adjustable mechanical properties, intrinsic flexibility, stretchability, transparency, and diverse functional and structural designs. Considerable efforts focus on developing CHs incorporating various conductive materials to enable multifunctional wearable sensors and flexible electrodes, such as metals, carbon, ionic liquids (ILs), MXene, etc. This review presents a comprehensive summary of the recent advancements in CHs, focusing on their classifications and practical applications. Firstly, CHs are categorized into five groups based on the nature of the conductive materials employed. These categories include polymer-based, carbon-based, metal-based, MXene-based, and ionic CHs. Secondly, the promising applications of CHs for electrophysiological signals and healthcare monitoring are discussed in detail, including electroencephalogram (EEG), electrocardiogram (ECG), electromyogram (EMG), respiratory monitoring, and motion monitoring. Finally, this review concludes with a comprehensive summary of current research progress and prospects regarding CHs in the fields of electronic skin and health monitoring applications. Full article

Clouds are important for Earth’s energy budget and water cycles, and precisely characterizing their vertical structure is essential for understanding their impact. Although passive remote sensing offers broad coverage and high temporal resolution, sensor and algorithmic limitations impede the accurate depiction of cloud vertical profiles. To improve estimates of their key structural parameters, e.g., cloud top height (CTH) and cloud vertical extent (CVE), we propose a multi-source collaborative optimization algorithm. The algorithm synergizes the wide-coverage FY-4A (FengYun-4A) and DSCOVR (Deep Space Climate Observatory) cloud products with high-precision CloudSat vertical profile data and establishes LightGBM-based CTH/CVE optimization models. The models effectively reduce systematic errors in the FY-4A and DSCOVR cloud products, lowering the CTH Mean Absolute Error (MAE) to 1.8 km for multi-layer clouds, an improvement of 4–8 km over the original. The CVE MAEs for single- and multi-layer clouds are ~2.5 km. Some bias remains in complex cases, e.g., multi-layer thin clouds at low altitudes, and error tracing analysis suggests this may be related to cloud layer number misclassification. The proposed algorithm facilitates daytime near-hourly cloud retrievals over China and neighboring regions. Full article

This study explores the use of embedded piezo sensor (EPS) employing the Electro-Mechanical Impedance (EMI) technique for real-time corrosion monitoring in reinforced E-waste concrete exposed to chloride-laden environments. With the growing environmental concerns over electronic waste (E-waste) and the demand for sustainable construction practices, printed circuit board (PCB) materials were incorporated as partial replacements for coarse aggregates in concrete. The experiment utilized M30-grade concrete mixes, substituting 15% of natural coarse aggregates with E-waste, aiming to assess both sustainability and structural performance without compromising durability. EPS configured with Lead Zirconate Titanate (PZT) patches were embedded into both conventional and E-waste concrete specimens. The EPS monitored the changes in the form of conductance and susceptance signatures across a 100–400 kHz frequency range during accelerated corrosion exposure over a 60-day period in a 3.5% NaCl solution. The corrosion progression was evaluated qualitatively through electrical impedance signatures, visually via rust formation and cracking, and quantitatively using the Root Mean Square Deviation (RMSD) of EMI signatures. The results showed that the EMI technique effectively captured the initiation and propagation stages of corrosion. E-waste concrete exhibited earlier and more severe signs of corrosion compared to conventional concrete, indicated by faster increases and subsequent declines in conductance and susceptance and higher RMSD values during the initiation phase. The EMI-based system demonstrated its capability to detect microstructural changes at early stages, making it a promising method for Structural Health Monitoring (SHM) of sustainable concretes. The study concludes that while the use of E-waste in concrete contributes positively to sustainability, it may compromise long-term durability in aggressive environments. However, the integration of EPS and EMI offers a reliable, non-destructive, and sensitive technique for real-time corrosion monitoring, supporting preventive maintenance and improved infrastructure longevity. Full article

A novel single-walled carbon nanotube (SWNT), silver (Ag) nanoparticle, and zinc benzene carboxylate (ZnBDC) metal–organic framework (MOF) composite was synthesised and systematically characterised to develop an efficient platform for mercury ion (Hg²⁺) detection. X-ray diffraction confirmed the successful incorporation of Ag nanoparticles and SWNTs without disrupting the crystalline structure of ZnBDC. Meanwhile, field-emission scanning electron microscopy and energy-dispersive spectroscopy mapping revealed a uniform elemental distribution. Thermogravimetric analysis indicated enhanced thermal stability. Electrochemical measurements (cyclic voltammetry and electrochemical impedance spectroscopy) demonstrated improved charge transfer properties. Electrochemical sensing investigations using differential pulse voltammetry revealed that the SWNTs/Ag@ZnBDC-modified glassy carbon electrode exhibited high selectivity toward Hg²⁺ ions over other metal ions (Cd²⁺, Co²⁺, Cr³⁺, Fe³⁺, and Zn²⁺), with optimal performance at pH 4. The sensor displayed a linear response in the concentration range of 0.1–1.0 nM (R² = 0.9908), with a calculated limit of detection of 0.102 nM, slightly close to the lowest tested point, confirming its high sensitivity for ultra-trace Hg²⁺ detection. The outstanding sensitivity, selectivity, and reproducibility underscore the potential of SWNTs/Ag@ZnBDC as a promising electrochemical platform for detecting trace levels of Hg2+ in environmental monitoring. Full article

The growing demand for the production of food has led to the development of new analytical techniques in the food industry, enabling innovative strategies to streamline food production and ensure its physicochemical and microbiological quality. In this work, a smart sensor was developed using the electrical impedance spectroscopy (EIS) technique. The system is based on discrete Fourier transform (DFT) and incorporates a Howland current source. The experimental results showed that the sensor was able to detect the moisture content in potatoes (Solanum tuberosum L.). Favorable responses were obtained by exciting the system with two frequency intervals: 0–100 Hz and 500–5000 Hz. An exhaustive analysis of the frequency response was performed to identify the most linear behavior in the moisture measurement, with an R-squared of 0.786 and signals in intervals from 500 to 5000 Hz. Moreover, the linearity remained stable across most frequencies, resulting in consistent measurements, even with the implementation of low-cost components. Full article

This work represents the first use of a phosphonium salt-functionalized β-Cyclodextrin polymer (β-CDP) as a highly selective sensing membrane for monitoring the safety of drinking water against perchlorate ions (ClO₄⁻) using electrochemical impedance spectroscopy (EIS). Structural confirmation via ¹H NMR, ¹³C NMR, ³¹P NMR, and FT-IR spectroscopies combined with AFM and contact angle measurements demonstrate how the enhanced solubility of modified cyclodextrin improves thin film quality. The innovation lies in the synergistic combination of two detection mechanisms: the “Host-Guest” inclusion in the cyclodextrin cavity and anionic exchange between the bromide ions of the phosphonium groups and perchlorate anions. Under optimized functionalization conditions, EIS reveals high sensitivity and selectivity, achieving a record-low detection limit (LOD) of ~10⁻¹² M and a wide linear range of detection (10⁻¹¹ M–10⁻⁴ M). Sensing mechanisms at the functionalized transducer interfaces are examined through numerical fitting of Cole-Cole impedance spectra via a single relaxation equivalent circuit. Real water sample analysis confirms the sensor’s practical applicability, with recoveries between 96.9% and 109.8% and RSDs of 2.4–4.8%. Finally, a comparative study with reported membrane sensors shows that β-CDP offers superior performance, wider range, higher sensitivity, lower LOD, and simpler synthesis. Full article

Oil condition monitoring can ensure the safe operation of mechanical equipment. Metal debris is full of friction information, and the identification of debris material helps to locate wear of parts. A method based on impedance analysis is proposed to identify debris material in this article. The differences in permeability and conductivity result in the nonlinear variation trend of inductance–resistance amplitude with debris volume. By establishing a database of amplitude–size curves, debris information (material and size) can be obtained through impedance analysis. Based on experimental and simulation results, iron, stainless steel, aluminum, copper, and brass particles are effectively distinguished. This method is not affected by oil’s light transmittance, other impurities, and debris surface dirt and can be used to distinguish metals with similar colors. This work provides a novel solution for debris material identification, which is expected to promote the development of fault diagnosis. Full article

Active power decoupling (APD) technology demonstrates significant advantages in addressing the mismatched second-order ripple power issue in single-phase rectifiers. However, conventional methods typically require additional voltage or current sensors to achieve precise decoupling control, thereby increasing the cost of the decoupling circuit. To reduce costs and simplify the control system, a sensor-reduced decoupling control method is proposed, with its key advantages highlighted in three aspects: First, the proposed method operates by replacing actual sampled variables with designed reference values, reducing the number of sensors—only the DC bus voltage information is required for operation. Second, the sensor-reduced control scheme is designed based on Lyapunov stability conditions and ensures system stability. Third, virtual impedance produces the reference current of the decoupling circuit, which eliminates grid signal interaction and simplifies control. Simulation and experimental results validate the effectiveness and feasibility of the proposed method. Full article