Search Results (439)

A novel glucose biosensor is developed based on a tilted fiber Bragg grating (TFBG) functionalized with a pH-responsive polyelectrolyte multilayer membrane, onto which glucose oxidase (GOD) is immobilized. The sensing film is constructed via layer-by-layer self-assembly of poly(ethylenimine) (PEI) and poly(acrylic acid) (PAA), which undergoes reversible swelling and refractive index (RI) changes in response to local pH variations. These changes are transduced into measurable shifts in the resonance wavelengths of TFBG cladding modes. The catalytic action of GOD oxidizes glucose to gluconic acid, thereby modulating the interfacial pH and actuating the polyelectrolyte membrane. With an optimized (PEI/PAA)₄(PEI/GOD)₁ structure, the biosensor achieves highly sensitive glucose detection, featuring a wide measurement range (10⁻⁸ to 10⁻² M), a low detection limit of 27.7 nM, and a fast response time of ~60 s. It also demonstrates excellent specificity and robust performance in complex biological matrices such as rabbit serum and artificial urine, with recovery rates of 93–102%, highlighting its strong potential for point-of-care testing applications. This platform offers significant advantages in stability, temperature insensitivity, and miniaturization, making it well-suited for clinical glucose monitoring and disease management. Full article

Precise control and monitoring systems are essential for efficient energy consumption in food dehydration. This study develops an applied cyber-physical control system to optimize food dehydration in rotary dryers, integrating fuzzy control algorithms through data acquisition. The system architecture utilizes DHT22 transducers for temperature monitoring, a DHT11 for humidity measurement, an IP65 anemometer for dryer wind speed detection, and a load cell weight tracking system, all connected to an Arduino Mega 2560 R3 microcontroller implementing the integrated fuzzy logic library. Experimental evaluations were performed with different carrot loads (1.5, 2.5, and 3.5 kg), demonstrating optimal performance at the initial load of 3.5 kg with an energy consumption of 11,589 kJ for 9.33 h, achieving a final moisture reduction of 10%. The 1.5 kg sample showed optimal dehydration kinetics at an average dryer hot air velocity of 1.5 m/s, while maximum efficiency (86%) was achieved with the 3.5 kg load, compared to 30% and 17% for the smaller batches. These results validate the integration of cyber-physical systems to optimize the dehydration rate (0.301 kg/h), thereby ensuring product quality in agro-industrial drying applications. Full article

This paper presents an analysis of the convergence of a numerical procedure used to evaluate the dynamic accuracy of measurement transducers, with particular emphasis on their application in energy and electromechanical systems. The main objective of the study is to assess the effectiveness of a fixed-point algorithm designed to determine test signals that satisfy time and amplitude constraints while maximizing an integral quality criterion of the “energy-optimal” type. The analysis employs numerical modeling of two types of temperature transducers: an NTC-type resistance temperature transducer and a K-type thermocouple. These models are based on a polynomial approximation method, enabling the estimation of the upper bound of the dynamic error—a key parameter in applications involving rapid changes in physical conditions, typical of energy and electromechanical systems operating under variable loads, such as industrial drives, clutches, bearings, and cooling systems, as well as in automation systems, control loops, and diagnostic frameworks. From the perspective of theoretical mechanics, temperature transducers can be modeled as a dynamic system characterized by thermal inertia, whose behavior is governed by first-order differential equations analogous to the equations of motion of a mass in a mechanically damped system. The results are presented graphically, illustrating the algorithm’s convergence behavior and computational stability. The practical application of the proposed approach can contribute to improving the accuracy of temperature transducers, enhancing error compensation algorithms, and optimizing the design of measurement systems in the energy sector and electromechanical industry, as well as in mechanical and electrical systems, especially where fast and reliable measurements under variable thermal loads on machine components are crucial. Full article

Compared with traditional piezoelectric transducers, Capacitive Micromachined Ultrasonic Transducers (CMUTs) have advantages such as better impedance matching with air, smaller size, lighter weight, higher sensitivity, and ease of array formation. Acoustic temperature measurement is a technology that utilizes the relationship between sound velocity and temperature to achieve non-contact temperature detection, with advantages such as fast response and non-invasiveness. CMUT-based acoustic temperature field measurement can achieve temperature detection in situations with narrow spaces, portability, and high measurement accuracy. This paper investigates an air-coupled CMUT device for acoustic temperature measurement, featuring a resonant frequency of 220 kHz, and composed of 16 × 8 cells. The design and fabrication of the CMUT array were completed, and the device characteristics were tested and characterized. A temperature field measurement method using mechanical scanning was proposed. A temperature measurement experimental system based on CMUT devices was constructed, achieving preliminary measurement of acoustic transmission time in both uniform and non-uniform temperature fields. Using a temperature field reconstruction algorithm, the measurement and imaging of the temperature field above an electric heating wire were accomplished and compared with the thermocouple-based temperature measurement experiment. The experimental results verified the feasibility of CMUT devices for non-contact temperature field measurement. Full article

The ultrasonic power supply constitutes the core component of an ultrasonic welding system, and its main function is to convert the industrial frequency electricity into resonant high-frequency electricity in order to achieve mechanical energy conversion. However, factors such as changes in ambient temperature or component aging may cause the resonant frequency of the transducer to drift, thus detuning the resonant system and seriously affecting system performance. Therefore, an ultrasonic welding system requires high-frequency tracking in real time. Traditional frequency tracking methods (such as acoustic tracking, PID control, etc.) have defects such as poor stability, narrow bandwidth, or cumbersome parameter setting, making it difficult to meet the demand for fast tracking. To address these problems, this study adopts a T-matching network and utilizes sliding mode control for frequency tracking. In order to solve the problems of slow convergence and obvious jitter in sliding mode control (SMC), a Hippopotamus Optimization (HO) algorithm is introduced to simulate hippopotamuses’ group behavior and predation mechanisms, thereby optimizing the control parameters. It is verified through simulation that the SMC algorithm optimized by the HO algorithm (HO-SMC) is able to suppress frequency drift more effectively and demonstrates the advantages of fast response, high accuracy, and strong robustness in the scenario of sudden load changes. Full article

Defensive pessimism, an important emotion regulation and motivation strategy, has increasingly attracted scholarly attention in psychology. Recently, sensor-based methods have begun to supplement or replace traditional questionnaire surveys in personality research. However, current approaches for collecting vital signs data face several challenges, including limited monitoring durations, significant data deviations, and susceptibility to external interference. This paper proposes a novel approach using a NiCr/NiSi alloy film temperature sensor, which has a K-type structure and flexible piezoelectric pressure sensor to identify and predict defensive pessimism personality traits. Experimental results indicate that the Seebeck coefficients for K-, T-, and E-type thermocouples are approximately 41 μV/°C, 39 μV/°C, and 57 μV/°C, respectively, which align closely with national standards and exhibit good consistency across multiple experimental groups. Moreover, radial artery frequency experiments demonstrate a strong linear relationship between pulse rate and the intensity of external stimuli, where stronger stimuli correspond to faster pulse rates. Simulation experiments further reveal a high correlation between radial artery pulse frequency and skin temperature, and a regression model based on the physiological sensor data shows a good fit (p < 0.05). These findings verify the feasibility of using temperature and flexible piezoelectric pressure sensors to identify and predict defensive pessimism personality characteristics. Full article

This paper presents the design, fabrication, and experimental evaluation of a capacitive micromachined ultrasonic transducer (CMUT) linear array for non-contact thickness measurement of marine engineering structures. A 16-element CMUT array was fabricated using a silicon–silicon wafer bonding process, and encapsulated in polyurethane to ensure acoustic impedance matching and environmental protection in underwater conditions. The acoustic performance of the encapsulated CMUT was characterized using standard piezoelectric transducers as reference. The array achieved a transmitting sensitivity of 146.82 dB and a receiving sensitivity of −229.55 dB at 1 MHz. A complete thickness detection system was developed by integrating the CMUT array with a custom transceiver circuit and implementing a time-of-flight (ToF) measurement algorithm. To evaluate environmental robustness, systematic experiments were conducted under varying water temperatures and salinity levels. The results demonstrate that the absolute thickness measurement error remains within ±0.1 mm under all tested conditions, satisfying the accuracy requirements for marine structural health monitoring. The results validate the feasibility of CMUT-based systems for precise and stable thickness measurement in underwater environments, and support their application in non-destructive evaluation of marine infrastructure. Full article

Dark asphalt surfaces, absorbing about 95% of solar radiation and warming to 60–70 °C during summer, intensify urban heat while providing substantial prospects for energy extraction. This review evaluates four primary technologies—asphalt solar collectors (ASCs, including phase change material (PCM) integration), photovoltaic (PV) systems, vibration-based harvesting, thermoelectric generators (TEGs)—focusing on their principles, efficiencies, and urban applications. ASCs achieve up to 30% efficiency with a 150–300 W/m² output, reducing pavement temperatures by 0.5–3.2 °C, while PV pavements yield 42–49% efficiency, generating 245 kWh/m² and lowering temperatures by an average of 6.4 °C. Piezoelectric transducers produce 50.41 mW under traffic loads, and TEGs deliver 0.3–5.0 W with a 23 °C gradient. Applications include powering sensors, streetlights, and de-icing systems, with ASCs extending pavement life by 3 years. Hybrid systems, like PV/T, achieve 37.31% efficiency, enhancing UHI mitigation and emissions reduction. Economically, ASCs offer a 5-year payback period with a USD 3000 net present value, though PV and piezoelectric systems face cost and durability challenges. Environmental benefits include 30–40% heat retention for winter use and 17% increased PV self-use with EV integration. Despite significant potential, high costs and scalability issues hinder adoption. Future research should optimize designs, develop adaptive materials, and validate systems under real-world conditions to advance sustainable urban infrastructure. Full article

Acoustic tweezers, as advanced micro/nano manipulation tools, play a pivotal role in biomedical engineering, microfluidics, and precision manufacturing. However, piezoelectric-based acoustic tweezers face performance limitations due to multi-physical coupling effects during microfabrication. This study proposes a novel approach using injection molding with embedded electronics (IMEs) technology to fabricate piezoelectric micro-ultrasonic transducers with micron-scale precision, addressing the critical issue of acoustic node displacement caused by thermal–mechanical coupling in injection molding—a problem that impairs wave transmission efficiency and operational stability. To optimize the IME process parameters, a hybrid multi-objective optimization framework integrating NSGA-II and MOPSO is developed, aiming to simultaneously minimize acoustic node displacement, volumetric shrinkage, and residual stress distribution. Key process variables—packing pressure (80–120 MPa), melt temperature (230–280 °C), and packing time (15–30 s)—are analyzed via finite element modeling (FEM) and validated through in situ tie bar elongation measurements. The results show a 27.3% reduction in node displacement amplitude and a 19.6% improvement in wave transmission uniformity compared to conventional methods. This methodology enhances acoustic tweezers’ operational stability and provides a generalizable framework for multi-physics optimization in MEMS manufacturing, laying a foundation for next-generation applications in single-cell manipulation, lab-on-a-chip systems, and nanomaterial assembly. Full article

Structural Health Monitoring (SHM) is an essential technique for continuously assessing structural conditions using integrated sensor systems during operation. SHM technologies have evolved to address the increasing demand for efficient maintenance strategies in advanced engineering fields, such as civil infrastructure, aerospace, and transportation. However, developing a miniaturized, cost-effective, and multi-sensor solution based on Wireless Sensor Networks (WSNs) remains a significant challenge, particularly for SHM applications in weight-sensitive aerospace structures. To address this, the present study introduces a novel WSN-based Multi-Sensor System (MSS) that integrates multiple sensing capabilities onto a 3 × 3 cm flexible Printed Circuit Board (PCB). The proposed system combines a Piezoelectric Transducer (PZT) for impact detection; a strain gauge for mechanical deformation monitoring; an accelerometer for capturing dynamic responses; and an environmental sensor measuring temperature, pressure, and humidity. This high level of functional integration, combined with real-time Data Acquisition (DAQ) and precise time synchronization via Bluetooth Low Energy (LE), distinguishes the proposed MSS from conventional SHM systems, which are typically constrained by bulky hardware, single sensing modalities, or dependence on wired communication. Experimental evaluations on composite panels and aluminum specimens demonstrate reliable high-fidelity recording of PZT signals, strain variations, and acceleration responses, matching the performance of commercial instruments. The proposed system offers a low-power, lightweight, and scalable platform, demonstrating strong potential for on-board SHM in aircraft applications. Full article

For non-destructive testing (NDT) of defects in aluminum alloy plates, traditional ultrasonic contact methods face challenges from high temperatures and liquid couplant contamination. Using electromagnetic acoustic transducers (EMATs), a key issue is that longitudinal waves (L-waves) excited by the butterfly-coil EMATs interfere with the desired shear waves (S-waves) reflected by internal defects. To solve this problem, a simulation–experiment approach optimized the butterfly coil parameters. An FE model visualized the electromagnetic acoustic transducer (EMAT) acoustic field and predicted signals. Orthogonal simulations tested three main parameters: excitation frequency, wire diameter, and effective coil width. Tests on aluminum specimens with artificial defects used the optimized EMAT. Simulated and measured signals showed strong correlation, validating optimal parameters. The results confirmed suppressed L-wave interference and improved defect detection sensitivity, enabling detection of a 3 mm diameter flat-bottomed hole buried 37 mm deep. Full article

It has been theoretically suggested that the de Broglie wavelength of Li ions could become longer than the Li atomic distance in solid electrolytes under coherent acoustic phonons at room temperature when thermal noise is sufficiently suppressed by them. This suggests that some quantum effect of Li ions (not electrons) could appear under this condition, which could possibly result in the superconductivity of ⁶Li⁺ ions (bosons) in solid electrolytes at room temperature. A lower frequency of coherent phonons is better for this possibility. A mechanism for the generation of coherent phonons by repetitive pulsed-laser irradiation or possibly by ultrasound irradiation using a transducer is also discussed. Full article

In the context of autonomous environmental monitoring, this study investigates a surface acoustic wave (SAW) sensor designed for selective carbon dioxide (CO₂) detection. The sensor is based on a LiTaO₃ piezoelectric substrate with copper interdigital transducers and a polyetherimide (PEI) layer, chosen for its high electromechanical coupling and strong CO₂ affinity. Finite element simulations were conducted to analyze the resonance frequency response under varying gas concentrations, film thicknesses, pressures, and temperatures. Results demonstrate a linear and sensitive frequency shift, with detection capability starting from 10 ppm. The sensor’s autonomy is ensured by a piezoelectric energy harvester composed of a cantilever beam structure with an attached seismic mass, where mechanical vibrations induce stress in a piezoelectric layer (PZT-5H or PVDF), generating electrical energy via the direct piezoelectric effect. Analytical and numerical analyses were performed to evaluate the influence of excitation frequency, material properties, and optimal load on power output. This integrated configuration offers a compact and energy-independent solution for real-time CO₂ monitoring in low-power or inaccessible environments. Full article

Accurate measurement of atmospheric turbulent fluctuations is critical for understanding environmental dynamics and improving models in applications such as wind energy. Advanced remote sensing technologies are essential for capturing instantaneous velocity and temperature fluctuations. Acoustic tomography (AT) offers a promising approach that utilizes sound travel times between an array of transducers to reconstruct turbulence fields. This study presents a systematic evaluation of the time-dependent stochastic inversion (TDSI) algorithm for AT using synthetic travel-time measurements derived from large-eddy simulation (LES) fields under both neutral and convective atmospheric boundary-layer conditions. Unlike prior work that relied on field observations or idealized fields, the LES framework provides a ground-truth atmospheric state, enabling quantitative assessment of TDSI retrieval reliability, sensitivity to travel-time measurement noise, and dependence on covariance model parameters and temporal data integration. A detailed sensitivity analysis was conducted to determine the best-fit model parameters, identify the tolerance thresholds for parameter mismatch, and establish a maximum spatial resolution. The TDSI algorithm successfully reconstructed large-scale velocity and temperature fluctuations with root mean square errors ($RMSE\mathrm{s}$) below 0.35 m/s and 0.12 K, respectively. Spectral analysis established a maximum spatial resolution of approximately 1.4 m, and reconstructions remained robust for travel-time measurement uncertainties up to 0.002 s. These findings provide critical insights into the operational limits of TDSI and inform future applications of AT for atmospheric turbulence characterization and system design. Full article

This paper presents advancements in structural health monitoring (SHM) techniques, with a particular focus on wave-screening methods for assessing prestress loss in a large-scale prestressed concrete (PC) bridge model under outdoor conditions. The wave-screening process utilizes low-frequency wave propagation obtained from seismic interferometry of structural free vibrations and high-frequency wave propagation obtained through ultrasonic transducers embedded in the structure. An adjustable post-tensioning system was employed in a series of experiments to simulate prestress loss. By comparing bridge vibrations under varying post-tensioning forces, the study investigated prestress loss and examined temperature-related effects using the coda wave interferometry (CWI) method. Local structural alterations were analyzed through wave velocity variations, demonstrating sensitivity to bridge temperature changes. The findings indicate that wave-based methods are more effective than traditional modal analysis for damage detection, highlighting the dual impacts of prestress loss and temperature, as well as damage localization. This study underscores the need for long-term measurements to account for temperature fluctuations when analyzing vibration measurements to investigate changes in prestressing force in PC structures. Full article