Search Results (267)

This paper presents a theoretical model of a thin, penny-shaped piezoelectric actuator bonded to an isotropic thermo-elastic substrate under coupled electrical-thermal-diffusive loading. The problem is assumed to be axisymmetric, and the peeling stress of the film is neglected in accordance with membrane theory, yielding a simplified equilibrium equation for the piezoelectric film. By employing potential theory and the Hankel transform technique, the surface strain of the substrate is analytically derived. Under the assumption of perfect bonding, a governing integral equation is established in terms of interfacial shear stress. The solution to this integral equation is obtained numerically using orthotropic Chebyshev polynomials. The derived results include the interfacial shear stress, stress intensity factors, as well as the radial and hoop stresses within the system. Finite element analysis is conducted to validate the theoretical predictions. Furthermore, parametric studies elucidate the influence of material mismatch and actuator geometry on the mechanical response. The findings demonstrate that, the performance of the piezoelectric actuator can be optimized through judicious control of the applied electrical-thermal-diffusive loads and careful selection of material and geometric parameters. This work provides valuable insights for the design and optimization of piezoelectric actuator structures in practical engineering applications. Full article

Actuators and power electronics are fundamental components of modern control systems, enabling high-precision functionality, enhanced energy efficiency, and sophisticated automation. This study investigates evolving research trends and thematic developments in these areas spanning the last two decades (2005–2024). This study analyzed 1840 peer-reviewed abstracts obtained from the Web of Science database using BERTopic modeling, which integrates transformer-based sentence embeddings with UMAP for dimensionality reduction and HDBSCAN for clustering. The approach also employed class-based TF-IDF calculations, intertopic distance visualization, and hierarchical clustering to clarify topic structures. The analysis revealed a steady increase in research publications, with a marked surge post-2015. From 2005 to 2014, investigations were mainly focused on established areas including piezoelectric actuators, adaptive control, and hydraulic systems. In contrast, the 2015–2024 period saw broader diversification into new topics such as advanced materials, robotic mechanisms, resilient systems, and networked actuator control through communication protocols. The structural topic analysis indicated a shift from a unified to a more differentiated and specialized spectrum of research themes. This study offers a rigorous, data-driven outlook on the increasing complexity and diversity of actuator and power electronics research. The findings are pertinent for researchers, engineers, and policymakers aiming to advance state-of-the-art, sustainable industrial technologies. Full article

Continuous monitoring of environmental and physiological parameters is essential for early diagnostics, real-time decision making, and intelligent system adaptation. Recent advancements in bio-microelectromechanical systems (BioMEMS) sensors have significantly enhanced our ability to track key metrics in real time. However, continuous monitoring demands sustainable energy supply solutions, especially for on-site energy replenishment in areas with limited resources. Artificial intelligence (AI), particularly large language models, offers new avenues for interpreting the vast amounts of data generated by these sensors. Despite this potential, fully integrated systems that combine self-powered BioMEMS sensing with AI-based analytics remain in the early stages of development. This review first examines the evolution of BioMEMS sensors, focusing on advances in sensing materials, micro/nano-scale architectures, and fabrication techniques that enable high sensitivity, flexibility, and biocompatibility for continuous monitoring applications. We then examine recent advances in energy harvesting technologies, such as piezoelectric nanogenerators, triboelectric nanogenerators and moisture electricity generators, which enable self-powered BioMEMS sensors to operate continuously and reducereliance on traditional batteries. Finally, we discuss the role of AI in BioMEMS sensing, particularly in predictive analytics, to analyze continuous monitoring data, identify patterns, trends, and anomalies, and transform this data into actionable insights. This comprehensive analysis aims to provide a roadmap for future continuous BioMEMS sensing, revealing the potential unlocked by combining materials science, energy harvesting, and artificial intelligence. Full article

The identification of structural damage types remains a key challenge in electromechanical impedance/admittance (EMI/EMA)-based structural health monitoring realm. This paper proposed a damage classification approach for concrete structures by using integrating discrete wavelet transform (DWT) decomposition of EMA signatures with supervised machine learning. In this approach, the EMA signals of arranged piezoelectric ceramic (PZT) patches were successively measured at initial undamaged and post-damaged states, and the signals were decomposed and processed using the DWT technique to derive indicators including the wavelet energy, the variance, the mean, and the entropy. Then these indicators, incorporated with traditional ones including root mean square deviation (RMSD), baseline-changeable RMSD named RMSDk, correlation coefficient (CC), and mean absolute percentage deviation (MAPD), were processed by a support vector machine (SVM) model, and finally damage type could be automatically classified and identified. To validate the approach, experiments on a full-scale reinforced concrete (RC) slab and application to a practical tunnel segment RC slab structure instrumented with multiple PZT patches were conducted to classify severe transverse cracking and minor crack/impact damages. Experimental and application results cogently demonstrated that the proposed DWT-based approach can precisely classify different types of damage on concrete structures with higher accuracy than traditional ones, highlighting the potential of the DWT-decomposed EMA signatures for damage characterization in concrete infrastructure. Full article

This paper proposes an Adam-optimized Deep Belief Networks (Adam-DBNs) denoising method for throat-attached piezoelectric signals. The method aims to process mechanical vibration signals captured through polyvinylidene fluoride (PVDF) sensors attached to the throat region, which are typically contaminated by environmental noise and physiological noise. First, the short-time Fourier transform (STFT) is utilized to convert the original signals into the time–frequency domain. Subsequently, the masked time–frequency representation is reconstructed into the time domain through a diagonal average-based inverse STFT. To address complex nonlinear noise structures, a Deep Belief Network is further adopted to extract features and reconstruct clean signals, where the Adam optimization algorithm ensures the efficient convergence and stability of the training process. Compared with traditional Convolutional Neural Networks (CNNs), Adam-DBNs significantly improve waveform similarity by 6.77% and reduce the local noise energy residue by 0.099696. These results demonstrate that the Adam-DBNs method exhibits substantial advantages in signal reconstruction fidelity and residual noise suppression, providing an efficient and robust solution for throat-attached piezoelectric sensor signal enhancement tasks. Full article

This paper presents a modeling framework for hysteretically nonlinear piezoelectric composite beams using functional differential equations (FDEs). While linear piezoelectric models are well established, they fail to capture the complex nonlinear behaviors that emerge at higher electric field strengths, particularly history-dependent hysteresis effects. This paper develops a cascade model that integrates a high-dimensional linear piezoelectric composite beam representation with a nonlinear Krasnosel’skii–Pokrovskii (KP) hysteresis operator. The resulting system is formulated using a state-space model where the input voltage undergoes a history-dependent transformation. Through modal expansion and discretization of the Preisach plane, we derive a tractable numerical implementation that preserves essential nonlinear phenomena. Numerical investigations demonstrate how system parameters, including the input voltage amplitude, and hysteresis parameters significantly influence the dynamic response, particularly the shape and amplitude of limit cycles. The results reveal that while the model accurately captures memory-dependent nonlinearities, it depends on numerous real and distributed parameters, highlighting the need for efficient reduced-order modeling approaches. This work provides a foundation for understanding and predicting the complex behavior of piezoelectric systems with hysteresis, with potential applications in vibration control, energy harvesting, and precision actuation. Full article

This paper considers the uniaxial orientation effect on the structure and piezoelectric properties of vinylidene fluoride-tetrafluoroethylene copolymer ferroelectric films. The films were exposed to uniaxial orientation stretching in a temperature range from 20 °C to 60 °C; then, they were contact polarized under normal conditions. The temperature dependence of the electric strength was determined. The longitudinal piezoelectric coefficient d₃₃ values were measured by the quasi-static Berlincourt method. The piezoresponse force microscopy (PFM) method was used to investigate the film domain structure before and after polarization, and the local piezoelectric coefficient values were also calculated. Phase composition was studied using differential scanning calorimetry and infrared spectroscopy with the Fourier transform. It was found that uniaxial orientation stretching contributed to an increase in the piezoelectric coefficient d₃₃ from 5 pC/N to 16–20 pC/N. The results obtained indicate the importance of the amorphous phase contribution to the formation of the piezoelectric properties in polymeric materials. Full article

This study examines how the frequency of an innovative energy harvester is tuned and how it behaves. This harvester transforms thermal energy into mechanical oscillations of two polyvinylidene fluoride (PVDF) piezoelectric beams, which produce electrical energy via a shape memory alloy (SMA) thread. The oscillation frequency is modified by two magnetic weights that are positioned symmetrically on the SMA thread and interact with stationary NdFeB permanent magnets. The SMA thread shifts laterally due to longitudinal thermal contraction and expansion induced by a constant-temperature heater. Temperature gradients above the heater trigger cyclical variations in the length of the SMA thread, leading to autonomous vibrations of the masses in both the vertical and horizontal planes. An experimental apparatus was constructed to analyze the harvester by tracking the motions of the masses and the voltages produced by the piezoelectric beams. Information was gathered regarding the correlation between output voltage and power with the consumer’s load resistance. These outcomes were confirmed using a multiphysics dynamic simulation that incorporated the interconnections among mechanical, thermal, magnetic, and electrical systems. The findings indicate that the use of permanent magnets increases the bending vibration frequency from 8.3 Hz to 9.2 Hz. For a heater maintained at 70 °C, this boosts the output power from 1.9 µW to 8.18 µW. A notable property of the considered energy harvester configuration is its ability to operate at cryogenic temperatures. Full article

This study presents the experimental results of an energy harvesting system comprising a cylindrical bluff body coupled with a cantilever beam. A piezoelectric sensor was installed on the beam to generate electrical voltage during the object’s vibrations at the beam’s free end. The research aimed to evaluate the impact of the bluff body’s mass and diameter on the efficiency of the piezoelectric energy harvesting system. Vibrations of the test object were induced by airflow within a chamber of a closed-loop wind tunnel. Five different bluff body masses were analyzed for each of three cylindrical diameters across an airflow velocity range of 1 m/s to 10 m/s. These experiments allowed for the recording of a series of voltage signals over time. The signals were then subjected to Fast Fourier Transform (FFT) analysis. Subsequently, the relationship between vibration frequency and airflow velocity was examined. The peak-to-peak voltage value was also analyzed to provide an overall assessment of the energy harvesting efficiency of the system under investigation. Finally, the 0–1 test for chaos was additionally employed as a diagnostic tool to assess the complexity of system dynamics based on time series data. This test allowed for distinguishing between oscillatory behavior and cases where the system became trapped in a potential well, revealing key transitions in dynamic regimes. Full article

Piezoelectric polyvinylidene fluoride (PVDF) film sensors embedded in a tire can make the tire have a sense of tactile. Thus, PVDF strain sensors play an important role in smart tires. However, temperature tolerance of PVDF is a key issue limiting its application in smart tire as the embedding process needs high temperature vulcanization. This paper proposes a film repolarization method to treat PVDF film materials after high temperature vulcanization, which can be implemented to apply in smart tire. Variation in piezoelectric properties and its changing mechanism of PVDF film are analyzed with the methods of X-Ray Diffraction Spectroscopy (XRD) and Fourier Transform Infrared Spectroscopy (FTIR). Vulcanization process that PVDF film sensors undergo in tire applications are simulated. Furthermore, properties of the PVDF sensors with different process stages are simulated based on finite element model. An experimental platform of the PVDF sensors is set up and the drop rod experiments are conducted. Results verify the performance improvement of the repolarization strategy on embedded PVDF sensors. The effectiveness of the repolarization in the PVDF film shows a great significance for the application of strain sensors in smart tire. Full article

Electroactive polymers (EAPs) have emerged as versatile materials for self-powered actuators and biosensors, revolutionizing biomedical diagnostics and healthcare technologies. These materials harness various energy harvesting mechanisms, including piezoelectricity, triboelectricity, and ionic conductivity, to enable real-time, energy-efficient, and autonomous sensing and actuation without external power sources. This review explores recent advancements in EAP-based self-powered systems, focusing on their applications in biosensing, soft robotics, and biomedical actuation. The integration of nanomaterials, flexible electronics, and wireless communication technologies has significantly enhanced their sensitivity, durability, and multifunctionality, making them ideal for next-generation wearable and implantable medical devices. Additionally, this review discusses key challenges, including material stability, biocompatibility, and optimization strategies for enhanced performance. Future perspectives on the clinical translation of EAP-based actuators and biosensors are also highlighted, emphasizing their potential to transform smart healthcare and bioelectronic applications. Full article

Nanogenerators have garnered significant scholarly interest as a groundbreaking approach to energy harvesting, encompassing applications in self-sustaining electronics, biomedical devices, and environmental monitoring. The rise of additive manufacturing has fundamentally transformed the production processes of nanocomposites, allowing for the detailed design and refinement of materials aimed at optimizing energy generation. This review presents a comprehensive analysis of 3D-printed nanocomposites in the context of nanogenerator applications. By employing layer-by-layer deposition, multi-material integration, and custom microstructural architectures, 3D-printed nanocomposites exhibit improved mechanical properties, superior energy conversion efficiency, and increased structural complexity when compared to their conventionally manufactured counterparts. Polymers, particularly those with inherent dielectric, piezoelectric, or triboelectric characteristics, serve as critical functional matrices in these composites, offering mechanical flexibility, processability, and compatibility with diverse nanoparticles. In particular, the careful regulation of the nanoparticle distribution in 3D printing significantly enhances piezoelectric and triboelectric functionalities, resulting in a higher energy output and greater consistency. Recent investigations into three-dimensional-printed nanogenerators reveal extraordinary outputs, encompassing peak voltages of as much as 120 V for BaTiO₃-PVDF composites, energy densities surpassing 3.5 mJ/cm², and effective d₃₃ values attaining 35 pC/N, thereby emphasizing the transformative influence of additive manufacturing on the performance of energy harvesting. Furthermore, the scalability and cost-effectiveness inherent in additive manufacturing provide substantial benefits by reducing material waste and streamlining multi-phase processing. Nonetheless, despite these advantages, challenges such as environmental resilience, long-term durability, and the fine-tuning of printing parameters remain critical hurdles for widespread adoption. This assessment highlights the transformative potential of 3D printing in advancing nanogenerator technology and offers valuable insights into future research directions for developing high-efficiency, sustainable, and scalable energy-harvesting systems. 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

Aiming at the issues of low sensitivity and poor resistance to temperature and vibration interference in traditional optical fiber current transformers, as well as the structural complexity of magnetostrictive material-coupled sensors, this paper integrates a high-sensitivity electrostrictive piezoelectric ceramic sensor with an FBG-FP cascaded fiber-optic sensor. This coupling significantly optimizes the sensor structure. By employing orthogonal intensity demodulation to enhance detection sensitivity, and adopting a multi-cycle waveform-averaging method to calculate the DC output light intensity, temperature calibration and compensation are achieved through the correlation between the DC output light intensity and operating points. Experimental results demonstrate that the designed sensor exhibits a detection bandwidth of 0–7 kHz, fully meeting the requirements for power-frequency current detection. Its current measurement range spans 0.15–42 mA, with a minimum measurable current as low as 150 μA. This study provides a compact, high-precision, highly scalable, and adaptable current detection solution for power systems, demonstrating significant engineering application value. Full article

The growing global demand for sustainable energy solutions has led to increased interest in kinetic energy harvesting as a viable alternative to traditional power sources. High-foot-traffic environments, such as public spaces and religious sites, generate significant mechanical energy that often remains untapped. This study explores energy-harvesting technologies applicable to public areas with heavy foot traffic, focusing on Al-Haram Mosque in Saudi Arabia—one of the most densely populated religious sites in the world. The research investigates the potential of piezoelectric, triboelectric, and hybrid systems to convert pedestrian foot traffic into electrical energy, addressing challenges such as efficiency, durability, scalability, and integration with existing infrastructure. Piezoelectric materials, including PVDF and BaTiO₃, effectively convert mechanical stress from footsteps into electricity, while triboelectric nanogenerators (TENGs) utilize contact electrification for lightweight, flexible energy capture. In addition, this study examines material innovations such as 3D-printed biomimetic structures, MXene-based composites (MXene is a two-dimensional material made from transition metal carbides, nitrides, and carbonitrides), and hybrid nanogenerators to improve the longevity and scalability of energy-harvesting systems in high-density footfall environments. Proposed applications for Al-Haram Mosque include energy-harvesting mats embedded with piezoelectric and triboelectric elements to power IoT devices, LED lighting, and environmental sensors. While challenges remain in material degradation, scalability, and cost, emerging hybrid systems and advanced composites present a promising pathway toward sustainable, self-powered infrastructure in large-scale, high-foot-traffic settings. These findings offer a transformative approach to energy sustainability, reducing reliance on traditional energy sources and contributing to Saudi Arabia’s Vision 2030 for renewable energy adoption. Full article