Search Results (572)

Capacitive micromachined ultrasonic transducers (CMUTs) have been widely applied in fields such as air-coupled ultrasonic nondestructive testing, gesture recognition, and 3D imaging. However, most current CMUTs struggle to simultaneously achieve both low power consumption and high performance, which limits their application in relevant fields. In this paper, a dual-layer CMUT is proposed, and its structural optimization design is also analyzed. The dual-layer CMUT consists of a top-layer circular CMUT cell and a bottom-layer annular CMUT cell. A movable pillar connects the top and bottom cells of the double-layer CMUT. This design increases the total deflection and reduces the stiffness, making the membrane more susceptible to deformation under external forces, thereby achieving low power consumption and high reception performance. The finite element method (FEM) results showed that, compared with conventional CMUTs, the structural optimization design of the dual-layer CMUT had a 13.7% reduction in collapse voltage. The improvements in the maximum deflection, average deflection, electromechanical coupling coefficient, transmitting sensitivity, and receiving sensitivity were 41.2%, 68.0%, 84.6%, 17.7%, and 101.6%, respectively. Therefore, the dual-layer CMUT has low power consumption and high reception performance while maintaining transmission performance, and it has potential for applications in portable, low-power devices and air-coupled ultrasonic nondestructive testing. Full article

This study presents a comprehensive multi-objective optimization framework specifically designed for micro-electromechanical systems (MEMS). The framework integrates both traditional and adaptive optimization techniques, named Surrogate-Assisted Multi-Objective Optimization (SAMOO) and Adaptive-SAMOO (A-SAMOO), respectively. By addressing key limitations of traditional approaches, such as the consideration of objective constraints and the provision of multiple design options, the proposed framework enhances both flexibility and practical applicability. Results show that adaptive optimization outperforms traditional offline methods by delivering a greater number and higher quality of optimal solutions while requiring fewer finite element method simulations. The adaptive approach showed a significant advantage by attaining high-quality solutions while requiring only 2.8% of the finite element method (FEM) evaluations compared to traditional methods that do not incorporate surrogate models. This performance boost highlights the advantages of online learning in enhancing the accuracy, speed, and diversity of solutions in MEMS optimization. These optimization schemes were tested on multiple MEMS devices with varying physics and complexities, specifically the U-shaped Lorentz force actuator, serpentine Lorentz force actuator, and thermal actuator. The results highlight the robustness and versatility of the proposed methods, particularly in addressing cases involving discrete design variables and strict objective constraints. This comprehensive, step-by-step framework serves as a valuable resource for researchers and practitioners aiming to optimize MEMS designs from the ground up, providing a reliable and effective approach to multi-objective optimization in MEMS applications. Full article

Autonomous vehicles are increasingly being adopted, with manufacturers competing to enhance automation capabilities. While full automation eliminates human input, lower levels still require driver intervention under specific conditions. This study presents the design and development of a prototype vehicle featuring both low- and high-level control systems, integrated with a 5G-based teleoperation interface that enables seamless switching between autonomous and remote-control modes. The system includes a malfunction surveillance unit that monitors communication latency and obstacle conditions, triggering a hardware-based emergency braking mechanism when safety thresholds are exceeded. Field experiments conducted over four test phases around Chulalongkorn University demonstrated stable performance under both driving modes. Mean lateral deviations ranged from 0.19 m to 0.33 m, with maximum deviations up to 0.88 m. Average end-to-end latency was 109.7 ms, with worst-case spikes of 316.6 ms. The emergency fallback system successfully identified all predefined fault conditions and responded with timely braking. Latency-aware stopping analysis showed an increase in braking distance from 1.42 m to 2.37 m at 3 m/s. In scenarios with extreme latency (>500 ms), the system required operator steering input or fallback to autonomous mode to avoid obstacles. These results confirm the platform’s effectiveness in real-world teleoperation over public 5G networks and its potential scalability for broader deployment. Full article

Designing and manufacturing devices at the micro- and nanoscales offers significant advantages, including high precision, quick response times, high energy density ratios, and low production costs. These benefits have driven extensive research in micro-electromechanical systems (MEMS) and nano-electromechanical systems (NEMS), resulting in various classifications of materials and manufacturing techniques, which are ultimately used to produce different classifications of MEMS devices. The current work aims to systematically organize the literature on MEMS in biomedical devices, encompassing past achievements, present developments, and future prospects. This paper reviews the current research trends, highlighting significant material advancements and emerging technologies in biomedical MEMS in order to meet the current challenges facing the field, such as ensuring biocompatibility, achieving miniaturization, and maintaining precise control in biological environments. It also explores projected applications, including use in advanced diagnostic tools, targeted drug delivery systems, and innovative therapeutic devices. By mapping out these trends and prospects, this review will help identify current research gaps in the biomedical MEMS field. By pinpointing these gaps, researchers can focus on addressing unmet needs and advancing state-of-the-art biomedical MEMS technology. Ultimately, this can lead to the development of more effective and innovative biomedical devices, improving patient care and outcomes. Full article

While extensive research has addressed electromechanical systems interacting with power electronic converters, most studies lack a unified modeling framework that simultaneously captures converter switching behavior, nonlinear dynamics, and linearized control-oriented representations. In particular, the dynamic interaction between two-level full-bridge converters and angular-motion electromechanical switching devices (EMDs) is often simplified or abstracted, thereby limiting control system design and frequency-domain analysis. This work presents a comprehensive dynamic modeling methodology for an angular-motion EMD driven by a full-bridge dc-dc converter. The modeling framework includes (i) a detailed nonlinear switching model, (ii) an averaged nonlinear model suitable for control design, and (iii) a small-signal linearized model for deriving transfer functions and evaluating system stability. The proposed models are rigorously validated through time-domain simulations and Bode frequency analysis, confirming both theoretical equilibrium points and dynamic characteristics such as resonant frequencies and phase margins. The results demonstrate strong consistency across the modeling hierarchy and reveal critical features—such as ripple-induced resonance and low-frequency coupling—that are essential for robust controller design. This framework established a foundational tool for advancing the control and optimization of electromechanical switching systems in high-performance applications. Full article

A wall-climbing robot is an electromechanical device capable of autonomous or semi-autonomous movement on intricate vertical surfaces (e.g., walls, glass facades, pipelines, ceilings, etc.), typically incorporating sensing and adaptive control systems to enhance task performance. It is designed to perform tasks such as inspection, cleaning, maintenance, and rescue while maintaining stable adhesion to the surface. Its applications span various sectors, including industrial maintenance, marine engineering, and aerospace manufacturing. This paper provides a systematic review of the physical principles and scalability of various attachment methods used in wall-climbing robots, with a focus on the applicability and limitations of different attachment mechanisms in relation to robot size and structural design. For specific attachment methods, the design and compatibility of motion and attachment mechanisms are analyzed to offer design guidance for wall-climbing robots tailored to different operational tasks. Additionally, this paper reviews localization and path planning methods for wall-climbing robots, comparing graph search, sampling-based, and feedback-based algorithms to guide strategy selection across varying environments and tasks. Finally, this paper outlines future development trends in wall-climbing robots, including the diversification of locomotion mechanisms, hybridization of attachment systems, and advancements in intelligent localization and path planning. This work provides a comprehensive theoretical foundation and practical reference for the design and application of wall-climbing robots. Full article

This study examined the relationship between front crawl trunk incline and the lower limbs’ biomechanics in non-expert swimmers. Eighteen male participants (19.22 ± 1.11 years) were recorded in the sagittal plane performing 2 × 25 m of front crawl at maximum intensity to analyze their trunk incline (TI), maximum knee angle (KneeMax), minimum knee angle (KneeMin), knee range of motion (KneeROM), kicking duration (KickDur), descendent phase duration (DurDesc), and ascendant phase duration (DurAsc). They also performed towing for passive drag measurements and a 20 s lower limbs’ tethered test while connected to an electromechanical device and grabbing a floating board to collect the maximum (Fmax) and mean (Fmean) kicking forces. Pearson’s correlation coefficient (r) was used to compute the relationships between all variables. For kinematics, a negative association was found between the TI and v (r = −0.64), KneeMin (r = −0.68), KneeRoM (r = −0.74), and SI (r = −0.52). Regarding kinetics, a single association was found between TI and Fmean (r = −0.52). The results indicate that a greater TI in non-expert swimmers may be a consequence of weaker knee action, which compromises their mean force application and negatively affects velocity and efficiency. Full article

Flexoelectricity arises in materials under strain gradients, which can be particularly significant for situations in which the existence of other electromechanical properties is absent or generating large flexoelectric properties is achievable. This effect has also been observed in some biological materials, whose understanding can hugely help to further enhance our understanding of vital biological processes like mechanotransduction, as well as the development of applications in regenerative medicine and drug delivery. While the field of flexoelectricity as a relevant topic in biological materials is relatively new and still developing, the current study aims to review available results on flexoelectric effects in biological materials such as cells and cell membranes, hearing mechanisms, and bone, and their potential applications in biomedical research. Therefore, we first provide a brief background on two main electromechanical couplings (piezoelectricity and flexoelectricity) and further, how flexoelectricity has been experimentally and theoretically identified. We then review flexoelectricity in different biological materials as the main aim of the current study. Within that, we provide additional emphasis on the influence of this effect on bone and bone remodeling. In particular, the study outlines current limitations and provides potential directions for future work, emphasizing the crucial role in the development of next-generation electromechanical devices and optimizing their function in the area of biomedical research. Full article

In the context of new power systems, the safe and accurate sensing of voltage data is crucial for the secure and stable operation of power grids. Given that existing voltage measurement devices cannot meet the development requirements for wide-area deployment and distributed monitoring, this paper designs a non-intrusive voltage measurement device based on MEMS (micro-electromechanical system) electric field sensors, which are characterized by their small size, low power consumption, ease of installation and strong anti-interference ability. Firstly, the paper introduces the voltage measurement principle and analyzes the equivalent circuit based on this analysis; secondly, the key structural design of the measurement device is completed and the prototype of the device is developed; finally, the accuracy and anti-jamming tests of the measurement device are conducted by establishing an experimental platform, followed by field applications. Experimental results demonstrate that the voltage measurement device has high measurement accuracy, and the maximum error is only 1.215%. Additionally, the device has a good shielding capability against the coupled electric field of surrounding interference conductors, with a maximum error increase of 1.313%. In a 10 kV overhead line voltage test, the device can accurately obtain the actual voltage. The voltage measuring device developed in this paper can provide data support for the condition assessment of overhead lines and effective monitoring means for the safe and stable operation of the power system. Full article

The increasing complexity of highway electromechanical systems has created a critical need to improve the accuracy of resource consumption standards. Traditional deterministic methods often fail to capture inherent variability in resource usage, resulting in significant discrepancies between budget estimates and actual costs. To address this issue for a specific device, this study develops a probabilistic framework based on Monte Carlo simulation, using manual barrier gate installation as a case study. First, probability distribution models for key parameters were established by collecting and statistically analyzing field data. Next, Monte Carlo simulation generated 100,000 pseudo-observations, yielding mean labor consumption of 1.08 workdays (SD 0.29), expansion bolt usage of 6.02 sets (SD 0.97), and equipment shifts of 0.20 (SD 0.10). Comparison with the “Highway Engineering Budget Standards” (JTG/T 3832-2018) revealed deviations of 1% to 4%, and comparison with market bid prices showed errors below 2%. These results demonstrate that the proposed method accurately captures dynamic fluctuations in resource consumption, aligning with both national norms and actual tender data. In conclusion, the framework offers a robust and adaptable tool for cost estimation and resource allocation in highway electromechanical projects, enhancing budgeting accuracy and reducing the risk of cost overruns. Full article

This paper focuses on the mathematical and numerical modeling of a non-classical macro fiber composite (MFC) piezoelectric transducer, MFC-P2, integrated with an aluminum cantilever beam for energy harvesting applications. It seeks to harness the transverse vibration energy in the environment to power small electronic devices, such as wireless sensors, where conventional power sources are inconvenient. The P2-type macro fiber composites (MFC-P2) are specifically designed for transverse energy harvesting applications. They offer high electric source capacitance and improved electric charge generation due to the strain developed perpendicularly to the voltage produced. The system is modeled analytically using Euler–Bernoulli beam theory and piezoelectric constitutive equations, capturing the electromechanical coupling in the d31 mode. Numerical simulations are conducted using COMSOL Multiphysics 6.29 to reduce the complexity of the mathematical model and analyze the effects of material properties, geometric configurations, and excitation conditions. The theoretical model is based on the transverse vibrations of a cantilevered beam using Euler–Bernoulli theory. The natural frequencies and mode shapes for the first four are determined. Depending on these, the resonance frequency, voltage, and power outputs are evaluated across a 12 kΩ resistive load. The results demonstrate that the energy harvester effectively operates near its fundamental resonant frequency of 10.78 Hz, achieving the highest output voltage of approximately 0.1952 V and a maximum power output of 0.0031 mW. The generated power is sufficient to drive ultra-low-power devices, validating the viability of MFC-based cantilever structures for autonomous energy harvesting systems. The application of piezoelectric phenomena and obtaining electrical energy from mechanical vibrations can be powerful solutions in such systems. The application of piezoelectric phenomena to convert mechanical vibrations into electrical energy presents a promising solution for self-powered mechatronic systems, enabling energy autonomy in embedded sensors, as well as being used for structural health monitoring applications. Full article

Industrial motors generate vibration energy that can be converted into electrical energy using piezoelectric vibration energy harvesters (pVEHs). These energy harvesters can power devices or function as self-powered sensors. However, optimal electromechanical designs of pVEHs are required to improve their output performance under different vibration frequency and amplitude conditions. To address this challenge, we performed the electromechanical modeling of a multilayer pVEH that harvests vibration energy from induction electric motors at frequencies close to 30 Hz. In addition, a parametric analysis of the geometry of the multilayer piezoelectric device was conducted to optimize its deflection and output voltage, considering the substrate length, piezoelectric patch position, and dimensions of the central hole. Our analytical model predicted the deflection and first bending resonant frequency of the piezoelectric device, with good agreement with predictions from finite element method (FEM) models. The proposed piezoelectric device achieved an output voltage of 143.2 V and an output power of 3.2 mW with an optimal resistance of 6309.5 kΩ. Also, the principal stresses of the pVEH were assessed using linear trend analysis, finding a safe operating range up to an acceleration of 0.7 g. The electromechanical design of the pVEH allowed for effective synchronization with the vibration frequency of an induction electric motor. This energy harvester has a potential application in industrial electric motors to transform their vibration energy into electrical energy to power sensors. Full article

Flexible capacitive pressure sensors (CPSs) have been widely studied and applied due to their various advantages. Numerous studies have been carried out on improving their electromechanical sensing properties through microporous structures. However, it is challenging to effectively control these structures. In this work, we controllably fabricate a hierarchical microporous capacitive pressure sensor (HMCPS) using melt near-field electro-writing technology. Thanks to the hierarchical microporous sensor, which provides a multi-level elastic modulus and relative dielectric constants, the HMCPS shows outstanding sensing properties. Its multi-range pressure response is sensitive: 3.127 kPa⁻¹ at low pressure, 0.124 kPa⁻¹ at medium pressure, and 0.025 kPa⁻¹ at high pressure. Also, it has a stability of over 5000 cycles and a response time of less than 100 ms. The HMCPS can monitor dynamic and static pressures across a broad pressure range. It has been successfully applied to monitor human motions, showing great potential in human–computer interaction and smart wearable devices. Full article

The growing demand for sustainable and self-powered technologies in automotive applications has led to increased interest in energy harvesting from vehicle suspensions. Recovering mechanical energy from road-induced vibrations offers a viable solution for powering wireless sensors and autonomous electronic systems, reducing dependence on external power sources. This study presents the design, modeling, and experimental validation of a hybrid energy-harvesting system that integrates piezoelectric and magnetoelectric effects to efficiently convert mechanical vibrations into electrical energy. A model-based systems engineering (MBSE) approach was used to optimize the system architecture, ensuring high energy conversion efficiency, durability, and seamless integration into suspension systems. The theoretical modeling of both piezoelectric and magnetoelectric energy harvesting mechanisms was developed, providing analytical expressions for the harvested power as a function of system parameters. The designed system was then fabricated and tested under controlled mechanical excitations to validate the theoretical models. Experimental results demonstrate that the hybrid system achieves a maximum power output of 16 µW/cm² from the piezoelectric effect and 3.5 µW/cm² from the magnetoelectric effect. The strong correlation between theoretical predictions and experimental measurements confirms the feasibility of this hybrid approach for self-powered automotive applications. Full article

In recent years, implantable medical devices (IMDs) have introduced groundbreaking solutions for managing various health conditions. However, traditional implanted batteries necessitate periodic surgical replacement and tend to be relatively bulky, posing significant inconvenience to patients. To overcome these limitations, researchers have investigated various wireless power transfer (WPT) techniques, among which the ultrasonic wireless power transmission (UWPT) technique has distinct advantages. However, limited research has been conducted on ultrasonic power transfer at lower operating frequencies. Therefore, this study explores wireless power transfer using scandium-doped aluminum nitride (AlScN) piezoelectric micro-electromechanical transducers (PMUTs) in deionized (DI) water. Experimental results indicate that at an operating frequency of 14.075 kHz, the power transfer efficiency (PTE) can reach up to 2.68% under optimal load resistance conditions. Furthermore, a low-frequency UWPT system based on a AlScN PMUT has been developed, delivering a stable 3.3 V output for implantable medical devices and contributing to the advancement of a full-spectrum UWPT framework. Full article