Search Results (42)

In this paper, we propose a real-time model estimation framework using artificial intelligence techniques and apply it to a piezoelectric transducer (PZT) stage equipped with multiple switching controllers. Conventional fixed controllers often fail to satisfy diverse performance requirements: some achieve smooth but slow responses, while others deliver fast yet oscillatory behavior. To address this limitation, we developed a multi-controller switching mechanism that can select optimal control sequences based on predicted system responses, thereby enhancing overall performance. However, the existing mechanism relies on a nominal plant and neglects variations during operation. To address this problem, we employ the eXtreme Gradient Boosting (XGBoost) algorithm to construct a real-time model estimator, which continuously updates the system model during response prediction, thereby improving prediction accuracy. The corresponding controllers are then adjusted according to the updated models and integrated into the switching mechanism to further enhance performance. Finally, we validate the proposed approach through simulations and experiments. Full article

The structural evolution of concrete during different hydration stages critically influences subsequent strength, and continuous monitoring throughout this process has become a research focus in materials science. This study proposes an embedded ultrasonic active sensing technique based on piezoelectric ceramics (PZT) to identify key structural transition stages during concrete curing. To this end, a piezoelectric ultrasonic sensor was fabricated and its comprehensive performance was systematically evaluated. Subsequently, compressive strength and penetration resistance tests were conducted, and the evolution of piezoelectric signal amplitude and wavelet packet energy (WPE) during hydration was analyzed. Furthermore, a root mean square deviation index based on WPE (WPE-RMSD) was introduced to identify structural transitions throughout the hydration process. The results demonstrate that the developed sensor exhibits stable electrical, mechanical, and waterproof performance. Both signal amplitude and WPE effectively captured the hydration process of concrete, with WPE showing higher sensitivity. The WPE-RMSD index exhibited good temporal continuity, covering the entire process from early hydration disturbance to late-stage structural densification (28 d), and proved particularly effective in identifying critical stages such as final setting and the medium-age period (7 d). This study provides a novel in situ monitoring approach for the classification and identification of hydration stages in concrete. Full article

This paper develops multiple control strategies for a precision long-travel stage, which comprises motor and piezoelectric transducer (PZT) stages. First, the PZT stage is equipped with control switching and model estimation mechanisms to achieve nm-level precision within 100 μm distances. The control switching mechanism selects the optimal control sequences by predicting system responses, while the model estimation algorithm updates the system model to improve the prediction accuracy. Second, the motor stage is equipped with gain-scheduling and feedforward control mechanisms to achieve a maximum displacement of 100 mm with a resolution of 0.1 μm. The gain scheduling control modifies the control gain in accordance with tracking errors, while the feedforward control can mitigate phase lags. We integrate the stages to achieve nm-level precision over long travels and conduct simulations and experiments to show the advantages of the control mechanisms. Finally, we apply the long-travel precision stage to fabricate micro-lenses using two-photon polymerization and evaluate the fabricated micro-lenses’ optical characteristics to illustrate the merits of the control strategies. Full article

This article presents a comprehensive investigation of the dynamic coupling between a piezoelectric actuator (PZT) and its driving nonlinear stiffness mechanism (NSM) stage for precise positioning control. Particular emphasis is placed on the preload-induced effects on the force transmission and structural separation between the PZT and NSM. To ensure continuous mechanical contact between them, we propose a no-separation criterion based on acceleration matching, from which the minimum preload requirement is analytically derived. Additionally, static and dynamic simulations reveal that increasing the preload force from 0 N to 10 N can push the first natural frequency of the holistic system from $214.21$ Hz to $258.17$ Hz, respectively. This beneficially enhances the displacement consistency across different geometric configurations. Moreover, an appropriate preload force can prevent separation and increase system stiffness while reducing nonlinear deformation. Experimental results verifies that a preload of 10 N can prevent the separation between the PZT and NSM stage and maintain achievable output displacement of the stage within the range from $54.35\mathsf{\mu }$m to $129.42\mathsf{\mu }$m. This article offers the analytical results of preload setting to guarantee reliable actuation for nonlinear precision positioning stages. 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

The need to strengthen the existing reinforced concrete (RC) elements is becoming increasingly crucial for modern cities as they strive to develop resilient and sustainable structures and infrastructures. In recent years, various solutions have been proposed to limit the undesirable effects of corrosion in RC elements. While C-FRP has shown promise in corrosion-prone environments, its use in structural applications is limited by cost, bonding, and anchorage challenges with concrete. To address these, the present research investigates the structural performance of RC beams reinforced with C-FRP bars under static loading using Structural Health Monitoring (SHM) with an Electro-Mechanical Impedance (EMI) system employing Lead Zirconate Titanate (PZT) piezoelectric transducers which are applied to detect damage development and enhance the protection of RC elements and overall, RC structures. This study underscores the potential of C-FRP bars for durable tensile reinforcement in RC structures, particularly in hybrid designs that leverage steel for compression strength. The study focuses on critical factors such as stiffness, maximum load capacity, deflection at each loading stage, and the development of crack widths, all analyzed through voltage responses recorded by the PZT sensors. Particular emphasis is placed on the bond conditions and anchorage lengths of the tensile C-FRP bars, exploring how local confinement conditions along the anchorage length influence the overall behavior of the beams. Full article

Real-time structural health monitoring (SHM) and accurate diagnosis of imminent damage are critical to ensure the structural safety of conventional reinforced concrete (RC) and fiber-reinforced concrete (FRC) structures. Implementations of a piezoelectric lead zirconate titanate (PZT) sensor network in the critical areas of structural members can identify the damage level. This study uses a recently developed PZT-enabled Electro-Mechanical Impedance (EMI)-based, real-time, wireless, and portable SHM and damage detection system in prismatic specimens subjected to flexural repeated loading plain concrete (PC) and FRC. Furthermore, this research examined the efficacy of the proposed SHM methodology for FRC cracking identification of the specimens at various loading levels with different sensor layouts. Additionally, damage quantification using values of statistical damage indices is included. For this reason, the well-known conventional static metric of the Root Mean Square Deviation (RMSD) and the Mean Absolute Percentage Deviation (MAPD) were used and compared. This paper addresses a reliable monitoring experimental methodology in FRC to diagnose damage and predict the forthcoming flexural failure at early damage stages, such as at the onset of cracking. Test results indicated that damage assessment is successfully achieved using RMSD and MAPD indices of a strategically placed network of PZT sensors. Furthermore, the Upper Control Limit (UCL) index was adopted as a threshold for further sifting the scalar damage indices. Additionally, the proposed PZT-enable SHM method for prompt damage level is first established, providing the relationship between the voltage frequency response of the 32 PZT sensors and the crack propagation of the FRC prisms due to the step-by-step increased imposed load. In conclusion, damage diagnosis through continuous monitoring of PZTs responses of FRC due to flexural loading is a quantitative, reliable, and promising application. Full article

This experimental study investigates the influence of synthetic macro-fibers added in fiber-reinforced concrete (FRC) prismatic specimens on their flexural response and overall cracking performance. Application of a novel structural health monitoring (SHM) system that implements the electromechanical impedance (EMI) technique and the use of piezoelectric lead zirconate titanate (PZT) transducers installed in the FRC prisms are also included. The applied PZT-enabled EMI-based monitoring system was developed to diagnose damage and the overall performance in reinforced concrete (RC) structural members subjected to cyclic repeated loading, simulating seismic excitations in existing RC buildings. The paper also aims to determine the sensitivity of the real-time, wireless, and portable monitoring technique corresponding to the location, the distance, the direction of polarization of the PZT transducers and the location and magnitude of damage due to flexural cracking. Further, the influence of the effect of stresses corresponding at various loading levels and the observed changes in the ΕΜΙ frequency response of the PZT transducers are also examined. Test results indicated that cracking detection is achieved using this SHM system by prompt damage level assessment due to the FRC’s flexural load at early seismic loading stages in existing RC buildings. Full article

Energy harvesters are autonomous systems capable of capturing, processing, storing, and utilizing small amounts of free energy from the surrounding environment. Such energy harvesters typically involve three fundamental stages: a micro-generator or energy transducer, a voltage booster or power converter, and an energy storage component. In the case of harvesting mechanical vibrations from the environment, piezoelectric materials have been used as a transducer. For instance, PZT (lead zirconate titanate) is a widely used piezoelectric ceramic due to its high electromechanical coupling factor. However, the integration of PZT into silicon poses certain limitations, not only in the harvesting stage but also in embedding a power management electronics circuit. On the other hand, in thermoelectric (TE) energy harvesting, a recent approach involves using abundant, eco-friendly, and low-cost materials that are compatible with CMOS technology, such as silicon-based compound nanostructures for TE thin film devices. Thus, this review aims to present the current advancements in the fabrication and integration of Si-based thin-film devices for TE energy harvesting applications. Moreover, this paper also highlights some recent developments in electronic architectures that aim to enhance the overall efficiency of the complete energy harvesting system. Full article

Recent advances both in hardware and software have facilitated the embedded intelligence (EI) research field, and enabled machine learning and decision-making integration in resource-scarce IoT devices and systems, realizing “conscious” and self-explanatory objects (smart objects). In the context of the broad use of WSNs in advanced IoT applications, this is the first work to provide an extreme-edge system, to address structural health monitoring (SHM) on polymethyl methacrylate (PPMA) thin-plate. To the best of our knowledge, state-of-the-art solutions primarily utilize impact positioning methods based on the time of arrival of the stress wave, while in the last decade machine learning data analysis has been performed, by more expensive and resource-abundant equipment than general/development purpose IoT devices, both for the collection and the inference stages of the monitoring system. In contrast to the existing systems, we propose a methodology and a system, implemented by a low-cost device, with the benefit of performing an online and on-device impact localization service from an agnostic perspective, regarding the material and the sensors’ location (as none of those attributes are used). Thus, a design of experiments and the corresponding methodology to build an experimental time-series dataset for impact detection and localization is proposed, using ceramic piezoelectric transducers (PZTs). The system is excited with a steel ball, varying the height from which it is released. Based on TinyML technology for embedding intelligence in low-power devices, we implement and validate random forest and shallow neural network models to localize in real-time (less than 400 ms latency) any occurring impacts on the structure, achieving higher than 90% accuracy. Full article

In this paper, we present a novel technique for passively autoranging a photonic current transducer (PCT) that incorporates a current transformer (CT), piezoelectric transducer (PZT) and fiber Bragg grating (FBG). Due to the usage of single-mode fiber and FBG, multiple PCTs can be interconnected and distributed over a long distance, for example along a power network, greatly reducing the cost of sensor deployment and offering other unique advantages. The autoranging technique relies on the usage of multiple, serially connected CT burden resistors and associated static MOSFET switches to realize instantaneous shortening of the resistors in response to increasing measured current. This functionality is realized passively, utilizing a modular, μW-power comparator circuit that powers itself from the electrical energy supplied by the CT within a small fraction of the 50/60 Hz cycle. The resultant instantaneous changes in sensor gain will be ultimately detected by the central FBG interrogator through real-time analysis of the optical signals and will be used to apply appropriate gain scaling for each sensor. The technique will facilitate the usage of a single PCT to cover an extended dynamic range of the measurement that is required to realize a combined metering- and protection-class current sensor. This paper is limited to the description of the design process, construction, and testing of a prototype passive autoranging circuitry for integration with the PCT. The two-stage circuitry that is based on two burden resistors, 1 Ω and 10 Ω, is used to prove the concept and demonstrate the practically achievable circuit characteristics. It is shown that the circuit correctly reacts to input current threshold breaches of approximately 2 A and 20 A within a 3 ms reaction time. The circuit produces distinct voltage dips across burden resistors that will be used for signal scaling by the FBG interrogator. Full article

The precise characterization and measurement of new nanomaterials and nano devices require in situ SEM nanorobotic instrumentation systems, which put forward further technical requirements on nanopositioning techniques of compact structure, cross-scale, nanometer accuracy, high vacuum and non-magnetic environment compatibility, etc. In this work, a novel cross-scale nanopositioning stage was proposed, which combined the advantages of piezoelectric stick-slip positioner and piezoelectric scanner techniques and adopted the idea of macro/micro positioning. A new structure design of a single flexible hinge shared by a small and large PZT was proposed to effectively reduce the size of the positioning stage and achieve millimeter stroke and nanometer motion positioning accuracy. Then, the cross-scale motion generation mechanism of the dual piezoelectric stick-slip drive was studied, the system-level dynamics model of the proposed positioning stages was constructed, and the mechanism design was optimized. Further, a prototype was manufactured and a series of experiments were carried out to test the performance of the stage. The results show that the proposed positioning stage has a maximum motion range of 20 mm and minimum step length of 70 nm under the small piezoceramic ceramic macro-motion stepping mode, and a maximum scanning range of 4.9 μm and motion resolution of 16 nm under the large piezoceramic ceramic micro-motion scanning mode. Moreover, the proposed stage has a compact structure size of 30 × 17 × 8 mm³, with a maximum motion speed of 10 mm/s and maximum load of 2 kg. The experimental results confirm the feasibility of the proposed stage, and nanometer positioning resolution, high accuracy, high speed, and a large travel range were achieved, which demonstrates that the proposed stage has significant performance and potential for many in situ SEM nanorobotic instrument systems. Full article

Outstanding ferroelectric and piezoelectric properties of PbZr_xTi_1-xO₃ (PZT) make nano and sub-micrometer particles of this material interesting for future nanotechnological applications as well as for fundamental studies of ferroelectricity at the nanoscale. In the present work, the prospects of a new hydrothermal approach were explored to control the particle size, aggregation stage, and composition of the PZT with the target composition of Zr/Ti = 60/40 (x = 0.6). Starting with water-soluble Zr-, Ti-, and Pb-precursors, the PZT formation was examined in the broad base (KOH) concentration range. The PZT particle size and composition were governed by the ratio of KOH with respect to Pb and not by the absolute KOH concentration (c_KOH). The incorporation of Zr into the PZT perovskite phase began to decline at KOH:Pb ≤ 1.7 and at KOH:Pb > 20. In the concentration range of 20 ≥ KOH:Pb > 1.5, the PZT particles adopted a cube-like shape, the size of which decreased with a decrease in the KOH:Pb ratio. The smallest (<200 nm) and well-separated PZT particles were obtained at KOH:Pb = 1.7. The prevailing PZT crystal structure at a Zr/Ti composition of around 60/40 was rhombohedral; the tetragonal phase also began to appear in Ti-richer PZT compositions (Zr/Ti ≤ 50/50). The developed understanding established the basis for further tailoring of PZT particle morphologies for application-oriented or fundamental research. Full article

The paper proposes a three-degrees-of-freedom flexible nano-positioning stage constructed from compliant flexures and piezoelectric thin-sheet actuators, featuring a compact size and fast dynamic responses, which can be extensively applied to the typical micro/nano-positioning applications. Meanwhile, the dynamic model of the flexible PZT nano-positioning with distributed parameter characteristics is established to distinctly reflect the piezoelectric–mechanical coupling relationship between the four flexible PZT actuators and the three outputs of such a system. Furthermore, the attitude decoupling control for the 3-DOF flexible piezoelectric nano-positioning stage is achieved by the Active Disturbance Rejection Control (ADRC) method to compensate for the positioning errors in the actual positioning process. After this, a real-time experimental apparatus with two Position-Sensitive Detectors (PSDs) is also proposed and fabricated to test the three outputs of the flexible piezoelectric thin-sheet (PZT-5A) nano-positioning stage and validate the effectiveness of the dynamic modeling method and attitude decoupling control in the piezoelectric nano-positioning stage ranges. Full article

This paper proposes a novel method for multi-class classification and uncertainty quantification of impact events on a flat composite plate with a structural health monitoring (SHM) system by using a Bayesian neural network (BNN). Most of the existing research in passive sensing has focused on deterministic approaches for impact detection and characterization. However, there are variability in impact location, angle and energy in real operational conditions which results in uncertainty in the diagnosis. Therefore, this paper proposes a reliability-based impact characterization method based on BNN for the first time. Impact data are acquired by a passive sensing system of piezoelectric (PZT) sensors. Features extracted from the sensor signals, such as their transferred energy, frequency at maximum amplitude and time interval of the largest peak, are used to develop a BNN for impact classification (i.e., energy level). To test the robustness and reliability of the proposed model to impact variability, it is trained with perpendicular impacts and tested by variable angle impacts. The same dataset is further applied in a method called multi-artificial neural network (multi-ANN) to compare its ability in uncertainty quantification and its computational efficiency against the BNN for validation of the developed meta-model. It is demonstrated that both the BNN and multi-ANN can measure the uncertainty and confidence of the diagnosis from the prediction results. Both have very high performance in classifying impact energies when the networks are trained and tested with perpendicular impacts of different energy and location, with 94% and 98% reliable predictions for BNN and multi-ANN, respectively. However, both metamodels struggled to detect new impact scenarios (angled impacts) when the data set was not used in the development stage and only used for testing. Including additional features improved the performance of the networks in regularization; however, not to the acceptable accuracy. The BNN significantly outperforms the multi-ANN in computational time and resources. For perpendicular impacts, both methods can reach a reliable accuracy, while for angled impacts, the accuracy decreases but the uncertainty provides additional information that can be further used to improve the classification. Full article