Search Results (300)

Concrete compressive strength is a critical property for structural performance and construction scheduling. Traditional non-destructive testing (NDT) methods, such as rebound hammer and ultrasonic pulse velocity, offer limited reliability and resolution, particularly at early ages. This study presents an AI-powered structural health monitoring (SHM) framework that integrates multi-type and multi-position piezoelectric (PZT) sensor networks with machine learning for in situ prediction of concrete compressive strength. Signals were collected from various PZT types positioned on the top, middle, bottom, and surface sides of concrete cubes during curing. A series of machine learning models were trained and evaluated using both the full and selected feature sets. Results showed that combining multiple PZT types and locations significantly improved prediction accuracy, with the best models achieving up to 95% classification accuracy using only the top 200 features. Feature importance and PCA analyses confirmed the added value of sensor heterogeneity. This study demonstrates that multi-sensor AI-enhanced SHM systems can offer a practical, non-destructive solution for real-time strength estimation, enabling earlier and more reliable construction decisions in line with industry standards. 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 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 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

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

Vibration energy offers promising potential for renewable energy harvesting, especially in conditions where conventional sources such as solar power may be limited or intermittent. This study proposes a rain energy harvester (REH) that converts the kinetic energy of raindrops into electrical energy using nonlinear thin plates, integrated with piezoelectric elements. Two plate configurations—fully hinged (H-H-H-H) and clamped–hinged–free–hinged (C-H-F-H)—are investigated. Theoretical modeling and simulation results are compared with experimental data, with special attention paid to the role of slapping forces in improving prediction accuracy. A power management system is also introduced to stabilize and regulate the harvested voltage. Results confirm the feasibility of rain-induced energy harvesting, showing potential for application in rain-prone areas and integration with existing infrastructure such as solar panels, tents, or canopies. Full article

Lead zirconate titanate (PZT) piezoelectric ceramics are widely used functional materials due to their strong and stable piezoelectric properties. A leveling method based on lead zirconate titanate piezoelectric ceramics is proposed for the high level of accuracy required in microelectromechanical fields such as aerospace, industrial robotics, biomedical, and photolithography. A leveling mechanism consisting of core components such as piezoelectric ceramic actuators and sensors is designed. The closed-loop leveling of the working platform is performed using the electromechanical coupling effect of the PZT piezoelectric material. Combined with the theory of the dielectric inverse piezoelectric effect in electric fields, a simulation is used to analyze the four force and deformation cases generated by the drive legs when the load is attached at different positions of the working platform, and the leveling is realized by applying the drive voltage to generate micro-motion displacement. Simulation and calculation results show that the leveling method can reduce the tilt angle of the working platform by 60% when the driving voltage is in the range of 10~150 V. The feasibility of the leveling method and the uniformity of the theoretical calculation and simulation are verified. Full article

This study presents the successful fabrication of lead zirconate titanate (PZT) thin films on silicon (Si) substrates using a hybrid deposition method combining spin-coating and RF sputtering techniques. Initially, a PZT layer was deposited through four successive spin-coating cycles, followed by an additional layer formed via RF sputtering. The resulting multilayer structure was annealed at ${700 }^{°}$C for 2 h to improve crystallinity. Comprehensive material characterization was conducted using XRD, SEM, cross-sectional SEM, EDX, and UV–VIS absorbance spectroscopy. The analyses confirmed the formation of a well-crystallized perovskite phase, a uniform surface morphology, and an optical band gap of approximately 3.55 eV, supporting its suitability for sensing applications. Building upon these findings, a multilayer PZT-based touch sensor was fabricated and electrically characterized. Low-frequency I–V measurements demonstrated consistent and repeatable polarization behavior under cyclic loading conditions. In addition, $\left|Z\right|$–f measurements were performed to assess the sensor’s dynamic electrical behavior. Although expected dielectric responses were observed, the absence of distinct anti-resonance peaks suggested non-idealities linked to ${\mathrm{Ag}}^{+}$ ion diffusion from the electrode layers. To account for these effects, the classical Butterworth–Van Dyke (BVD) equivalent circuit model was extended with additional inductive and resistive components representing parasitic pathways. This modified model provided excellent agreement with the measured impedance and phase data, offering deeper insight into the interplay between material degradation and electrical performance. Overall, the developed sensor structure exhibits strong potential for use in piezoelectric sensing applications, particularly for tactile and pressure-based interfaces. Full article

Piezoelectric energy harvesting in roadways can power distributed sensors and electronics by capturing underutilized mechanical energy from traffic. In this research, 1-3 stacked piezocomposites were developed and evaluated to determine optimal designs for multiple applications. The design of these transducers aimed at operating in a multitude of scenarios, under compressive loads (1–10 kN) at low-frequency (10 Hz) applications, intended to simulate vehicular forces. Power comparison was utilized between numerous transducers to determine the most efficient configuration for electromechanical energy conversion. Design guidelines were based on mechanical integrity, output power, active piezoelectric volume percentage, aspect ratio, and geometric factors. The forces applied in this study were reliant on the average vehicle weight. An intermediate PZT volume fraction and moderate pillar aspect ratios were found to yield the highest power output, with the stacked 1-3 composite significantly outperforming a monolithic PZT of a similar size. 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

This article investigates energy harvesting methods designed to capture energy from the alternating magnetic field surrounding a current-carrying conductor. The study focuses on the use of piezoelectric transducers in both monolithic and bimorph configurations. Experimental tests were conducted using vibrating beam structures composed of a single-layer piezoelectric material as well as bimorph piezoelectric composites, both utilizing lead zirconate titanate (PZT) as the active material. The results demonstrate a significant improvement in energy harvesting efficiency when using the bimorph configuration. Specifically, the bimorph-based system generated a peak voltage of 4.26 V and a current of 127.16 μA, resulting in an RMS power output of 272.48 μW. The operating principles, signal conditioning strategies, and structural differences in the evaluated designs are discussed in detail. The outcomes indicate the potential of such systems for powering autonomous sensors in low-power industrial monitoring applications. Full article

Interface debonding between high-strength grouting materials and the inner surfaces of steel tubes in grouting jacket connections (GJCs), which have been widely employed in offshore wind turbine support structures, negatively affects their mechanical behavior. In this study, an interface debonding defect detection and localization approach for scaled underwater GJC specimens using surface wave measurements with piezoelectric lead zirconate titanate (PZT) actuation and sensing technology was validated experimentally. Firstly, GJC specimens with artificially mimicked interface debonding defects of varying dimensions were designed and fabricated in the lab, and the specimens were immersed in water to replicate the actual underwater working environment of GJCs in offshore wind turbine structures. Secondly, to verify the feasibility of the proposed interface debonding detection approach using surface wave measurements, the influence of the height and circumferential dimension of the debonding defects on the output voltage signal of PZT sensors was systematically studied experimentally using a one pitch and one catch (OPOC) configuration. Thirdly, a one pitch and multiple catch (OPMC) configuration was further employed to localize and visualize the debonding defect regions. An abnormal value analysis was carried out on the amplitude of the output voltage signals from PZT sensors with identical wave traveling paths, and the corresponding abnormal surface wave propagation paths were identified. Finally, based on the influence of interface debonding on the surface wave measurements mentioned above, the mimicked interface debonding defect was detected successfully and the region of debonding was determined with the intersection of the identified abnormal wave travelling paths. The results showed that the mimicked debonding defect can be visualized. The feasibility of this method for interface debonding defect detection in underwater GJCs was confirmed experimentally. The proposed approach provides a novel non-destructive debonding defect detection approach for the GJCs in offshore wind turbine structures. Full article

Interface debonding between the steel tube and grouting materials in grouting jacket connections (GJCs) of offshore wind turbine supporting structures leads to negative effects on the load-carrying capacity and safety concerns. In this paper, an interface debonding defect detection and localization approach for scale underwater GJC specimens using surface wave measurement is proposed and validated numerically. A multi-physics finite element model (FEM) of underwater GJCs with mimicked interface debonding defects, surrounded by water, and coupled with surface-mounted piezoelectric lead zirconate titanate (PZT) patches is established. Under the excitation of a five-cycle modulated signal, the surface stress wave propagation, including transmission, diffraction, and reflection, within the outer steel tube, grouting material, and inner steel tube is simulated. The influence of mimicked interface debonding defects of varying dimensions on stress wave propagation is systematically analyzed through stress wave field distributions at distinct time intervals. Additionally, the response of surface-mounted PZT sensors in the underwater GJC model under a one-pitch-one-catch (OPOC) configuration is analyzed. Numerical results demonstrate that the wavelet packet energy (WPE) of the surface wave measurement from the PZT sensors corresponding to the traveling path with a mimicked interface debonding defect is larger than that without a defect. To further localize the debonding region, a one pitch and multiple catch (OPMC) configuration is employed, and an abnormal value analysis is conducted on the WPEs of PZT sensor measurements with identical and comparable wave traveling patches. The identified debonding regions correspond to the simulated defects in the models. Full article

Composites of ferromagnetic and ferroelectric phases are of interest for studies on mechanical strain-mediated coupling between the two phases and for a variety of applications in sensors, energy harvesting, and high-frequency devices. Nanocomposites are of particular importance since their surface area-to-volume ratio, a key factor that determines the strength of magneto-electric (ME) coupling, is much higher than for bulk or thin-film composites. Core–shell nano- and microcomposites of the ferroic phases are the preferred structures, since they are free of any clamping due to substrates that are present in nanobilayers or nanopillars on a substrate. This review concerns recent efforts on ME coupling in coaxial fibers of spinel or hexagonal ferrites for the magnetic phase and PZT or barium titanate for the ferroelectric phase. Several recent studies on the synthesis and ME measurements of fibers with nickel ferrite, nickel zinc ferrite, or cobalt ferrite for the spinel ferrite and M-, Y-, and W-types for the hexagonal ferrites were considered. Fibers synthesized by electrospinning were found to be free of impurity phases and had uniform core and shell structures. Piezo force microscopy (PFM) and scanning microwave microscopy (SMM) measurements of strengths of direct and converse ME effects on individual fibers showed evidence for strong coupling. Results of low-frequency ME voltage coefficient and magneto-dielectric effects on 2D and 3D films of the fibers assembled in a magnetic field, however, were indicative of ME couplings that were weaker than in bulk or thick-film composites. A strong ME interaction was only evident from data on magnetic field-induced variations in the remnant ferroelectric polarization in the discs of the fibers. Follow-up efforts aimed at further enhancement in the strengths of ME coupling in core–shell composites are also discussed in this review. Full article

This paper introduces a wearable silent text input system designed to capture text input through silent speech, without generating audible sound. The system integrates Electromyography (EMG) and piezoelectric lead zirconate titanate (PZT) sensors in a miniaturized form that can be comfortably attached to the chin, making it both comfortable to wear and esthetically pleasing. The EMG sensor records muscle activity linked to specific tongue and jaw movements, while the PZT sensor measures the minute vibrations and pressure changes in the chin skin caused by silent speech. Data from both sensors are analyzed to capture the timing and intensity of the silent speech signals, allowing the extraction of key features in both time and frequency domain. Several machine learning (ML) models, including both feature-based and non-feature-based approaches commonly used for classification tasks, are employed and compared to detect and classify subtle variations in sensor signals associated with individual alphabet letters. To evaluate and compare the ML models, EMG and PZT signals for the eight most frequently used English letters are collected across one hundred trials each. Results showed that non-feature-based models, particularly the Fea-Shot Learning with fused EMG and PZT signals, achieved the highest accuracy (95.63%) and F1-score (95.62%). The proposed system’s accuracy and real-time performance make it promising for silent text input and assistive communication applications. Full article