Search Results (1,003)

Two semiflexible piezoelectric composite plate structures were developed, incorporating 1 × 9 and 2 × 9 arrays of PZT elements mounted on brass discs and mechanically secured by pop rivets within a thin plastic foil spacer positioned between two copper-clad PCB layers. This configuration provides reliable electrical contact, adequate mechanical compliance, and efficient conversion of mechanical vibration energy into electrical energy. In addition, a multifunctional thermoelectric device was realized, consisting of four cubic modules arranged around a rectangular tube and enabling both handheld operation and coupling to hot or cold surfaces. Each cube is equipped with optimized finned heat sinks and integrates four thermoelectric elements on each face. Experimental results show that each cube generates approximately 6 mW, when handheld and with icy water injected into the central tube, demonstrating its suitability as a compact and versatile thermal energy harvester. Under low-light conditions, a solar panel is supplemented by this hybrid piezoelectric–thermoelectric energy harvesting system that combines the output of a piezoelectric composite plate with the dual outputs of a thermoelectric device using an electronically isolated summing block to ensure source decoupling. Energy storage and management are implemented using a capacitor buffer for the piezoelectric device, two voltage boosters for the thermoelectric outputs, and an automatic ultra-low-power pulse width modulation buck regulator for charging supercapacitors at 5 V. Full article

Combine harvesters are evolving from machines equipped with isolated monitoring devices into distributed sensing platforms for process supervision, machine diagnosis, and adaptive control. This review summarizes representative research on six major sensing tasks in combine harvesters: grain loss, grain breakage, cleaning load, feed rate, grain-bin state, and grain quality. The reviewed studies are compared within a unified engineering framework that considers sensing target, installation position, signal path, disturbance source, calibration transferability, field robustness, and control relevance. Rather than evaluating sensors only as individual devices, this review emphasizes the coupled design of transducers, structural anti-interference measures, sampling paths, signal processing, and field-oriented validation under vibration-dominated and dust-laden harvesting conditions. The analysis shows that loss-rate and feed-rate sensing are currently the most mature and control-relevant categories, whereas breakage-rate, grain-bin, and integrated quality sensing remain constrained by representative sampling, disturbance resistance, and cross-condition generalization. Future progress will depend on multi-sensor fusion, realistic benchmark protocols, crop-aware calibration transfer, and tighter integration among onboard sensing, machine control, and digital harvesting systems. By clarifying the engineering value of these sensing routes, the review also supports loss reduction, quality preservation, labor-saving operation, and more reliable adaptive control in commercial grain harvesting. Full article

This review provides a comprehensive synthesis of robotic fruit harvesting systems, with a particular focus on the system-level integration of perception, manipulation, and fruit detachment within autonomous harvesting environments. Recent advances in machine vision, deep learning, sensor fusion, robotic end-effectors, grasping strategies, and motion planning are critically analyzed alongside cutting, pulling, and vibration-based detachment mechanisms under unstructured orchard conditions. Beyond component-level analysis, this review emphasizes the critical role of perception–action coupling and highlights key system integration challenges, including localization errors, perception-to-action latency, and environmental variability, which continue to limit reliable field deployment. In addition, orchard and pre-harvest-related factors such as canopy structure, fruit distribution, and detachment force variability are examined in relation to their direct impact on system performance, robustness, and harvesting efficiency. Furthermore, the review extends toward system-level considerations by incorporating performance evaluation metrics, economic feasibility, and scalability constraints, which are essential for transitioning robotic harvesting systems from experimental prototypes to commercially viable solutions, including practical field deployment in distributed and multi-robot harvesting systems. Emerging technologies, including artificial intelligence, advanced sensing, digital agriculture, and energy-aware system design, are discussed as key enablers for achieving adaptive, data-driven, and scalable autonomous harvesting. The novelty of this work lies in proposing an integrated framework that explicitly links perception, manipulation, and detachment with orchard-level constraints and deployment requirements, thereby bridging the gap between algorithmic advancements and real-world implementation of autonomous fruit harvesting systems. Full article

During the harvest period, the role of lateral leaves in the dynamic behavior of the walnut (Juglans regia) branch–leaf–fruit subsystem remains unclear, and vibration harvesting parameter selection still lacks targeted guidance. To address this issue, a local walnut branch–leaf–fruit subsystem was studied by combining a discrete dynamic model, free-vibration tests, forced-vibration tests, and MATLAB simulations to investigate the effects of lateral leaf number on system dynamics. A representative single-fruit subsystem with six lateral leaves was selected, and four leaf number conditions (zero, two, four, and six) were examined. High-speed imaging was used to identify leaf motion patterns, while natural frequencies and fruit tracking point displacement responses were measured. The results showed that lateral leaves mainly exhibited three motion modes during vibration: spin, swing, and spin–swing compound motion. Under the six-leaf condition, spin motion was dominant. As the number of lateral leaves increased from 0 to 6, the first-order natural frequency decreased from 13.92 ± 6.37 Hz to 8.79 ± 4.03 Hz, a reduction of 36.8%. Forced-vibration results showed that increasing lateral leaf number significantly reduced the displacement response of the fruit tracking point in the non-excitation directions. Under the six-leaf condition, the maximum displacements in the Y- and Z-directions were reduced by 56.0% and 55.8%, respectively, compared with the leafless condition, indicating that the forced response became more concentrated in the main excitation direction. In the original MATLAB model, lateral leaves were simplified as fixed lumped mass damping elements, and the predicted results differed from the experimental trends. After introducing dynamic damping parameters matched to leaf motion patterns, the simulated trends became closer to the experimental results. These findings indicate that lateral leaf number is an important structural factor affecting the natural characteristics and directional forced responses of the walnut branch–leaf–fruit subsystem. The results provide theoretical and experimental references for optimizing vibration parameters and supporting low-damage, high-efficiency walnut vibration harvesting. Full article

In this work, a self-powered vibration sensing system is proposed, based on a spatial magnetic field energy harvester, a duty-cycled circuit module, a piezoresistive graphene-based vibration sensor, and a wireless communication unit. The energy harvester is capable of generating an output power of 729 μW under a magnetic field excitation of 0.11 mT at 50 Hz. The duty-cycled circuit module enables closed-loop self-powered operation of the sensing system by efficient power storage and periodic measurement, and LoRa wireless transmission. The graphene-based sensor exhibits stable low-frequency vibration responses and good linearity and can capture composite vibration signals containing 4 Hz and 50 Hz components. These results indicate the potential of the proposed system for future transmission-line vibration sensing applications. Full article

Focusing on the self-powering demand of aircraft engine bladed disks (blisks), this paper investigates piezoelectric vibration energy-harvesting modeling and non-linear circuit performance. A multi-sector electromechanical coupled model is established to analyze the frequency splitting and vibration localization induced by minor structural mistuning. By breaking the cyclic symmetry, mistuning severely concentrates vibration energy into a specific sector, providing a localized high-energy concentration region for optimal energy extraction. To enhance recovery efficiency and load adaptability, three interface circuit topologies—Standard Energy-Harvesting (SEH), Parallel Synchronized Switch Harvesting on Inductor (P-SSHI), and Double Synchronized Switch Harvesting (D-SSHI)—are comparatively analyzed. Through wideband spatial–spectral dynamic response and steady-state impedance matching analyses, the non-linear energy conversion and transfer mechanisms are systematically characterized. Results demonstrate that synchronized switching circuits significantly improve energy transmission via forced voltage inversion, accompanied by a notable equivalent stiffness enhancement effect induced by electromechanical coupling. Furthermore, the D-SSHI topology not only exhibits substantial advantages in peak power extraction, but also, owing to its internal LC energy decoupling mechanism, forms a broad load-independent power plateau across an extremely wide impedance range. This research provides robust theoretical foundations for designing highly resilient self-powered intelligent blades under extreme operating conditions. Full article

Although bistable vibration energy harvesters offer promising broadband characteristics, their efficiency is often hindered by fixed potential barriers that confine the system to small-amplitude intra-well motion. The core innovation of this work is the proposal of a synchronous potential barrier regulation mechanism for multiple subsystems based on a rhombus linkage mechanism. This study introduces a novel multi-subsystem bistable vibration energy harvester (MBEH) integrated with a rhombus linkage mechanism to achieve tunable potential barriers. The mechanism facilitates the coupling of four bistable subsystems, where adjusting the magnet spacing of one subsystem allows for the synchronous regulation of magnetic gaps in others. This architecture ensures a continuous and precise optimization of the potential barrier. Consequently, this mechanism yields remarkable performance advancements, achieving highly efficient coupling among subsystems. Furthermore, potential barrier regulation efficiency is substantially increased, while operating bandwidths of subsystems are complementary and superimposed. Results from numerical investigations indicate that at an excitation acceleration of 0.6 g, MBEH outperforms conventional BEH with a 13.58 Hz increase in summed subsystem bandwidth and a 0.0223 μW gain in output power. The findings validate the efficacy of the proposed MBEH as a high-performance solution for robust broadband vibration energy harvesting. Full article

To deliver freshwater for drip irrigation, our study presents an optimal techno-economic based on a Water Pumping Photovoltaic System (WPPVS) that integrates a Hydrogen Energy Storage System (HySS) to ensure reliable freshwater for agricultural irrigation in remote arid regions. A critical operational challenge in WPPVS is mechanical vibration at low flow rates, which degrades the pump efficiency and lifespan. Our methodology directly addresses this issue by incorporating a vibration-avoidance strategy that ensures that the pump operates only within its stable and, efficient range. To reduce the loss of water supply probability and overall annual costs of the drip irrigation system, a multi-objective optimization framework using Multi-Objective Particle Swarm Optimization (MOPSO) and Gaussian Mixture Model (GMM) clustering to simultaneously minimize the Loss of Water Supply Probability (LWSP), and the system’s total life-cycle cost. The model’s practical applicability is demonstrated through a detailed techno-economic feasibility analysis for a tomato crop drip irrigation project in Sakaka, Saudi Arabia. Sensitivity analysis is performed on dynamic head, crop prices, and interest and inflation rates, confirming the robustness of the system against variable economic indicators. In comparison to 1071 h without HySS, the results revealed that the seasonal irradiation harvest hours are 1863, which represents 21% of the seasonal hours employing the developed hybrid energy storage coordination. This integrated approach provides a holistic and economically viable solution for designing reliable solar irrigation systems with long-term mechanical integrity. Full article

Under low wind speed conditions, conventional bluff body energy harvesters suffer from a single vibration mechanism and a narrow effective wind speed range, making it difficult to meet the continuous power supply demands of miniature electronic devices. In this paper, by systematically optimizing the number of triangular prisms N and the circumferential installation angle α, a parametrically adjustable star-shaped energy harvester (SEH) is proposed. The proposed structure consists of a cylindrical base with a tunable number of triangular prisms uniformly distributed along its circumference, aiming to reveal the regulation mechanism of the VIV-galloping coupling response and energy harvesting performance. Conceptual design and theoretical modeling of the SEH are first carried out. Then, three-dimensional fluid–structure interaction simulations are performed by varying N and α, and a prototype is fabricated for wind tunnel experimental validation. The results show that under the optimal parameter combination of N = 7 and α = 51.4°, the SEH achieves a maximum output voltage of 12.2 V at a wind speed of 3.41 m/s, with a maximum output power of 1.488 mW, and the effective wind speed range is broadened to 2.5~12.44 m/s. Compared with the conventional cylindrical energy harvester (CEH), the SEH (N = 7) increases the maximum output voltage by 44.38%, the maximum output power by 108.4%, and expands the effective wind speed range by 198.50%. Through systematic optimization of key geometric parameters, this study achieves synergistic regulation of flow-induced vibration modes and performance enhancement, providing a parametric design basis for efficient low-speed wind energy harvesting, which can promote the development of self-powered technologies for micro-sensors and IoT devices. Full article

The open fan as a highly efficient propulsion concept is a promising approach to reduce climate-damaging emissions in aviation. However, the increased vibroacoustic emissions of the fan resulting from the open design lead to elevated cabin noise. Energy harvesting resonators can be used to leverage the piezoelectric effect and to attenuate structural vibrations caused by the acoustic loading simultaneously. To evaluate the potential of a specific configuration of energy harvesting resonators, an investigation of the dynamic interaction between the airframe and the resonators is necessary. Therefore, the eigenmodes and eigenfrequencies of a representative stiffened plate are determined experimentally using modal analysis via laser scanning vibrometry. A finite element model of the stiffened plate with the resonator idealized as a mass–spring element is implemented. The stiffness of this simplified resonator model is calibrated by correlating simulated with experimental results following a model updating approach. Finally, an optimization framework designed to determine the optimal quantity and placement of resonators using the experimentally validated model and representative loads is implemented to maximize both vibroacoustic attenuation and energy harvesting efficiency. The resulting framework serves as a generalized optimization tool capable of systematically optimizing the resonator configuration based on airframe geometry and specified vibroacoustic loading scenarios. Full article

To address the low mechanization level, high labor intensity, and severe substrate disturbance in intertidal shellfish harvesting, a vibratory harvesting method based on local vibration-induced substrate fluidization was proposed, and a vibratory harvesting device for Mactra veneriformis was developed. Bench and intertidal field tests were conducted to systematically investigate the effects of vibration frequency, vibration pressure, and vibration amplitude on substrate fluidization, clam uplift, and harvesting performance. The single-factor results showed that all three parameters significantly affected the pore water pressure ratio, substrate viscosity, uplift distance, and harvesting rate, with better fluidization obtained at 8 Hz, 30 kPa, and 25 mm. A Box–Behnken response surface design was further used to establish quadratic regression models for these responses, and all models were highly significant with a non-significant lack of fit. The optimized parameter combination was 10 Hz, 35 kPa, and 25 mm, under which the predicted pore water pressure ratio and uplift distance were 101.3% and 97.2 mm, respectively, and the substrate viscosity was 1364 Pa·s. Field tests showed that the pore water pressure ratio remained above 85.3%, viscosity decreased to 1331–2639 Pa·s, shear strength decreased by 57.2–64.9%, and the average uplift distance at 100 mm burial depth reached 80–92 mm. The results indicate that vibratory harvesting can effectively promote substrate fluidization and reduce clam uplift resistance, providing a reference for the development of low-disturbance mechanized harvesting equipment for intertidal shellfish. Full article

Mechanized harvesting in the industrial tomato sector is currently bottlenecked by excessive mechanical injuries and elevated levels of foreign materials generated during electro-mechanical combine harvesting operations. To combat these limitations, this comprehensive review explores recent breakthroughs in harvester-mounted smart grading systems engineered specifically for complex, open-field conditions. Rather than relying solely on conventional optical inspection, the study examines the transition toward advanced, heterogeneous edge-computing frameworks—incorporating FPGAs and embedded GPUs—deployed within electro-mechanical harvesting platforms. This architectural evolution plays a crucial role in mitigating unpredictable processing delays caused by intense operational vibrations, although achieving absolute real-time stability under extreme field conditions remains an ongoing challenge. To minimize bruising and physical deterioration, our analysis synthesizes findings from multi-scale explicit dynamic finite element simulations, unpacking the underlying microstructural failure modes of the crop. We illustrate how regulating applied forces via soft robotic effectors can help approach a ‘damage-free’ handling threshold, though empirical results vary depending on fruit maturity and dynamic operational speeds. Furthermore, coupling multi-modal sensor fusion with Convolutional Neural Networks (CNNs) shows promising potential for non-destructive internal property evaluation under the vibration, dust, and throughput constraints of electro-mechanical harvesters, pending broader validation across diverse field datasets. Ultimately, by projecting future trends in onboard electro-mechanical harvester separation and advocating for a closer synergy between agronomic practices and machine engineering, this paper delivers a comprehensive blueprint for building next-generation, highly resilient, and gentle sorting machinery. Full article

Artificial intelligence is transforming agriculture from a mechanized, labor-intensive sector into a data-driven, perception-enabled, and increasingly autonomous production system. In this review, AI serves as an umbrella term encompassing machine learning, computer vision, and robotic control, among other technologies. We synthesize recent advances across the tillage–sowing–management–harvesting (TSMH) workflow, covering intelligent tillage, precision sowing, field management, and robotic harvesting. The literature shows that AI has significantly improved agricultural perception, prediction, and task-level decision-making. However, large-scale adoption remains constrained by data heterogeneity, limited cross-scene generalization, environmental uncertainty, and insufficient integration across operational stages. Future progress will depend on multimodal data fusion, lightweight and interpretable models, cloud-edge collaboration, and full-chain decision architectures. By framing current research within the TSMH pipeline, this review highlights both technical advances and the critical bottlenecks that must be addressed to move smart agriculture from stage-specific intelligence toward system-level autonomy. Representative studies indicate that AI models can improve soil-property prediction and reduce sowing miss-detection rates to below 3% under controlled or bench-top conditions. However, field deployment may be affected by environmental variability, including illumination changes, dust, vibration, occlusion, and hardware constraints. These limitations highlight the need for robust and edge-compatible architectures. Full article

Vibration energy harvesting has emerged as a sustainable solution for powering low-energy devices such as wireless sensors and wearable electronics. However, conventional vibration energy harvesters often suffer from narrow operational bandwidth and limited output performance under ultra-low excitation conditions. To overcome these limitations, this study proposes an asymmetric tristable vibration energy harvester integrated with an elastic magnifier (EM), hereafter referred to as the asymmetric TVEH with EM, to enhance energy conversion efficiency under weak excitation. A nonlinear two-degree-of-freedom electromechanical model is developed to describe the coupled dynamics between the cantilever beam and the EM, incorporating nonlinear restoring forces and electromechanical coupling effects. The system performance is investigated using the harmonic balance method (HBM) and time-domain numerical simulations. In addition, parametric studies are conducted to examine the influence of the EM mass and stiffness ratios on the dynamic response and energy harvesting performance. The numerical results demonstrate that the inclusion of the EM significantly amplifies the system response under ultra-low excitation $(f=0.055)$, enabling improved inter-well motion and enhancing energy conversion efficiency by up to 45%. To validate the analytical and numerical findings, an experimental prototype is fabricated and tested. The experimental results confirm the effectiveness of the proposed design, achieving a root mean square voltage of $V_{\mathrm{rms}}=5\mathrm{V}$ across a load resistance of $R_L=100\mathrm{k}\mathrm{\Omega }$ under a base acceleration of $1.4{\mathrm{m}/\mathrm{s}}^2$ at 14 Hz, measured over a 30 s window with a low-pass filter cut-off frequency of 100 Hz. The proposed asymmetric TVEH with EM consistently outperforms both the symmetric TVEH with EM and the asymmetric configuration without EM. Overall, the results highlight the pivotal role of the elastic magnifier in enhancing the dynamic response and harvesting performance under weak excitations, demonstrating strong potential for powering low-power electronic devices in practical applications. Furthermore, this work supports the United Nations Sustainable Development Goal SDG 7 (Affordable and Clean Energy) by promoting decentralized and renewable vibration-based energy harvesting technologies. Full article