Search Results (879)

Complex mechanical systems, such as agricultural combine harvesters, are subjected to dynamic excitations from multiple coupled sources, compromising structural integrity and operational reliability. Disentangling these vibrations to identify dominant sources and quantify their transmission paths remains a significant engineering challenge. This study proposes a robust diagnostic framework to address this issue. We employed a multi-condition vibration test with sequential source activation and an improved Operational Transfer Path Analysis (OTPA) method. Applied to a harvester chassis, the results revealed that vibration energy is predominantly concentrated in the 0–200 Hz frequency band. Path contribution analysis quantified that the “cutting header → conveyor trough → hydraulic cylinder → chassis frame” path is the most critical contributor to vertical vibration, with a vibration acceleration level of 117.6 dB. Further analysis identified the engine (29.3 Hz) as the primary source for vertical vibration, while lateral vibration was mainly attributed to a coupled resonance between the threshing cylinder (58 Hz) and the engine’s second-order harmonic. This study’s theoretical contribution lies in validating a powerful methodology for vibration source apportionment in complex systems. Practically, the findings provide direct, actionable insights for targeted structural optimization and vibration suppression. Full article

Wireless sensor networks provide a solution for structural health monitoring of aviation pipelines. In the installation environment of aviation pipelines, widespread vibrations can be utilized to extract energy through vibration energy harvesting technology to achieve self-powering of sensors. This study analyzed the vibration characteristics of aviation pipeline structures. The vibration characteristics and influencing factors of typical aviation pipeline structures were obtained through simulations and experiments. An N-shaped symmetric vibration energy harvester was designed considering the limited space in aviation pipeline structures. To improve the efficiency of electrical energy extraction from the vibration energy harvester, expand its operating frequency band, and achieve efficient vibration energy harvesting, this study first analyzed its natural frequency characteristics through theoretical analysis. Finite element simulation software was then used to analyze the effects of the external excitation acceleration direction, mass and combination of counterweights, piezoelectric sheet length, and piezoelectric material placement on the output power of the energy harvester. The structural parameters of the vibration energy harvester were optimized, and the optimal working conditions were determined. The experimental results indicate that the N-shaped symmetric vibration energy harvester designed and optimized in this study improves the efficiency of vibration energy harvesting and can be arranged in the limited space of aviation pipeline structures. It achieves efficient energy harvesting under multi-modal conditions, different excitation directions, and a wide operating frequency band, thus meeting the practical application requirement and engineering feasibility of aircraft design. Full article

Dark asphalt surfaces, absorbing about 95% of solar radiation and warming to 60–70 °C during summer, intensify urban heat while providing substantial prospects for energy extraction. This review evaluates four primary technologies—asphalt solar collectors (ASCs, including phase change material (PCM) integration), photovoltaic (PV) systems, vibration-based harvesting, thermoelectric generators (TEGs)—focusing on their principles, efficiencies, and urban applications. ASCs achieve up to 30% efficiency with a 150–300 W/m² output, reducing pavement temperatures by 0.5–3.2 °C, while PV pavements yield 42–49% efficiency, generating 245 kWh/m² and lowering temperatures by an average of 6.4 °C. Piezoelectric transducers produce 50.41 mW under traffic loads, and TEGs deliver 0.3–5.0 W with a 23 °C gradient. Applications include powering sensors, streetlights, and de-icing systems, with ASCs extending pavement life by 3 years. Hybrid systems, like PV/T, achieve 37.31% efficiency, enhancing UHI mitigation and emissions reduction. Economically, ASCs offer a 5-year payback period with a USD 3000 net present value, though PV and piezoelectric systems face cost and durability challenges. Environmental benefits include 30–40% heat retention for winter use and 17% increased PV self-use with EV integration. Despite significant potential, high costs and scalability issues hinder adoption. Future research should optimize designs, develop adaptive materials, and validate systems under real-world conditions to advance sustainable urban infrastructure. Full article

The threshing drum, a core component in combine harvesters, experiences significant unbalanced vibrations during high-speed rotation, leading to severe mechanical wear, increased energy consumption, elevated noise levels, potential safety hazards, and higher maintenance costs. A primary challenge is that excessive interference signals often obscure the fundamental frequency characteristics of the vibration, hampering balancing effectiveness. This study introduces a signal conditioning model to suppress such interference and accurately extract the unbalanced quantities from the raw signal. Leveraging this extracted vibration force signal, an automatic optimization method for the balancing counterweights was developed, solving calculation issues inherent in traditional approaches. This formed the basis for an automatic balancing control strategy and an integrated system designed for online monitoring and real-time control. The system continuously adjusts the rotation angles, θ₁ and θ₂, of the balancing weight disks based on live signal characteristics, effectively reducing the drum’s imbalance under both internal and external excitation states. This enables a closed loop of online vibration testing, signal processing, and real-time balance control. Experimental trials demonstrated a significant 63.9% reduction in vibration amplitude, from 55.41 m/s² to 20.00 m/s². This research provides a vital theoretical reference for addressing structural instability in agricultural equipment. Full article

The urgent demand of wireless sensor nodes for long-life and maintenance-free miniature electrical sources with output power ranging from microwatts to milliwatts has accelerated the development of energy harvesting technologies. For the abundant and renewable nature of wind in environments, flow-induced vibration (FIV)-based wind energy harvesting has emerged as a promising approach. Electromagnetic FIV wind energy harvesters (WEHs) show great potential for realistic applications due to their excellent durability and stability. However, electromagnetic WEHs remain less studied than piezoelectric WEHs, with few dedicated review articles available. This review analyzes the working principle, device structure, and performance characteristics of electromagnetic WEHs based on vortex-induced vibration, galloping, flutter, wake galloping vibration, and Helmholtz resonator. The methods to improve the output power, broaden the operational wind speed range, broaden the operational wind direction range, and enhance the durability are then discussed, providing some suggestions for the development of high-performance electromagnetic FIV WEHs. 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

Magnetorheological (MR) foams represent a class of smart materials with unique tunable viscoelastic properties when subjected to external magnetic fields. Combining porous structures with embedded magnetic particles, these materials address challenges such as leakage and sedimentation, typically encountered in conventional MR fluids while offering advantages like lightweight design, acoustic absorption, high energy harvesting capability, and tailored mechanical responses. Despite their potential, challenges such as non-uniform particle dispersion, limited durability under cyclic loads, and suboptimal magneto-mechanical coupling continue to hinder their broader adoption. This review systematically addresses these issues by evaluating the synthesis methods (ex situ vs. in situ), microstructural design strategies, and the role of magnetic particle alignment under varying curing conditions. Special attention is given to the influence of material composition—including matrix types, magnetic fillers, and additives—on the mechanical and magnetorheological behaviors. While the primary focus of this review is on MR foams, relevant studies on MR elastomers, which share fundamental principles, are also considered to provide a broader context. Recent advancements are also discussed, including the growing use of artificial intelligence (AI) to predict the rheological and magneto-mechanical behavior of MR materials, model complex device responses, and optimize material composition and processing conditions. AI applications in MR systems range from estimating shear stress, viscosity, and storage/loss moduli to analyzing nonlinear hysteresis, magnetostriction, and mixed-mode loading behavior. These data-driven approaches offer powerful new capabilities for material design and performance optimization, helping overcome long-standing limitations in conventional modeling techniques. Despite significant progress in MR foams, several challenges remain to be addressed, including achieving uniform particle dispersion, enhancing viscoelastic performance (storage modulus and MR effect), and improving durability under cyclic loading. Addressing these issues is essential for unlocking the full potential of MR foams in demanding applications where consistent performance, mechanical reliability, and long-term stability are crucial for safety, effectiveness, and operational longevity. By bridging experimental methods, theoretical modeling, and AI-driven design, this work identifies pathways toward enhancing the functionality and reliability of MR foams for applications in vibration damping, energy harvesting, biomedical devices, and soft robotics. Full article

High-efficiency wind energy collection and precise wind vector monitoring are crucial for sustainable energy applications, smart agriculture, and environmental management. A novel multi-layered triboelectric–electromagnetic hybrid generator (TEHG) for broadband wind energy collection and wind vector monitoring was built. The TEHG comprises three functional layers corresponding to three modules: a soft-contact rotary triboelectric nanogenerator (S-TEHG), an electromagnetic generator (EMG), and eight flow-induced vibration triboelectric nanogenerators (F-TENGs), which are arranged in a circular array to enable low-wind-speed energy harvesting and multi-directional wind vector monitoring. The TEHG achieves broadband energy harvesting and demonstrates exceptional stability, maintaining a consistent electrical output after 3 h of continuous operation. The EMG charges a 1 mF capacitor to 1.5 V 738 times faster than conventional methods by a boost converter. The TEHG operates for 17.5 s to power a thermohygrometer for 103 s, achieving an average output power of 1.87 W with a power density of 11.2 W/m³, demonstrating an exceptional power supply capability. The F-TENGs can accurately determine the wind direction, with a wind speed detection error below 4.5%. This innovative structure leverages the strengths of both EMG and TENG technologies, offering a durable, multifunctional solution for sustainable energy and intelligent environmental sensing. 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 study presents an analytical and experimental approach to enhance cantilever-based piezoelectric energy harvesters by optimizing thickness distribution. Using a gradient projection algorithm within a state-space framework, the unimorph beam’s geometry is tailored while constraining the first natural frequency. The objective is to amplify axial strain within the piezoelectric layers, thereby increasing electric polarization and maximizing the conversion efficiency of mechanical vibrations into electrical energy. The steady-state response under harmonic base excitation at resonance was modeled to evaluate the harvester’s dynamic behavior against uniform-thickness counterparts. Results show that the optimized beam achieves significantly higher output voltage and energy harvesting efficiency. Simulations reveal effective strain concentration in regions of high piezoelectric sensitivity, enhancing power generation under resonant conditions. Two independent experimental setups were employed for empirical validation: a non-contact laser vibrometry system (Polytec 3D) and a first resonant base excitation setup. Eigenfrequencies matched within 5% using a Polytec multipath interferometry system, and constant excitation tests showed approximately 30% higher in optimal shapes electrical potential value generation. The outcome of this study highlights the efficacy of geometric tailoring—specifically, non-linear thickness shaping—as a key strategy in achieving enhanced energy output from piezoelectric harvesters operating at their fundamental frequency. This work establishes a practical route for optimizing unimorph structures in real-world applications requiring efficient energy capture from low-frequency ambient vibrations. Full article

Both ZnO and BeO semiconductors crystallize in the hexagonal wurtzite (wz), cubic rock salt (rs), and zinc-blende (zb) phases, depending upon their growth conditions. Low-dimensional heterostructures ZnO/Be_xZn_1-xO and Be_xZn_1-xO ternary alloy-based devices have recently gained substantial interest to design/improve the operations of highly efficient and flexible nano- and micro-electronics. Attempts are being made to engineer different electronic devices to cover light emission over a wide range of wavelengths to meet the growing industrial needs in photonics, energy harvesting, and biomedical applications. For zb materials, both experimental and theoretical studies of lattice dynamics ${\mathsf{\omega }}_{\mathrm{j}}\left(\overrightarrow{\mathrm{q}}\right)$ have played crucial roles for understanding their optical and electronic properties. Except for zb ZnO, inelastic neutron scattering measurement of ${\mathsf{\omega }}_{\mathrm{j}}\left(\overrightarrow{\mathrm{q}}\right)$ for BeO is still lacking. For the Be_xZn_1-xO ternary alloys, no experimental and/or theoretical studies exist for comprehending their structural, vibrational, and thermodynamical traits (e.g., Debye temperature ${\mathsf{\Theta }}_{\mathrm{D}}\left(\mathrm{T}\right);$ specific heat ${\mathrm{C}}_{\mathrm{v}}\left(\mathrm{T}\right))$. By adopting a realistic rigid-ion model, we have meticulously simulated the results of lattice dynamics, and thermodynamic properties for both the binary zb ZnO, BeO and ternary Be_xZn_1-xO alloys. The theoretical results are compared/contrasted against the limited experimental data and/or ab initio calculations. We strongly feel that the phonon/thermodynamic features reported here will encourage spectroscopists to perform similar measurements and check our theoretical conjectures. Full article

Based on the research of the directional self-adaptive piezoelectric energy harvester (DSPEH), a structural design scheme of a multi-directional hybrid energy harvester (MHEH) is put forward. The working principle of the MHEH is experimentally studied. A prototype is designed and manufactured, and the output characteristics of the MHEH in vibrational degree of freedom (DOF) and rotational DOF are experimentally studied. Compared with the DSPEH, after adding the electromagnetic energy harvesting module, the MHEH effectively uses the rotational energy in the rotational DOF, achieves simultaneous energy harvesting from one excitation through two mechanisms, and the output power of the electromagnetic module reaches 61 μW. The total power of the system is increased by 10 times, the power density is increased by 500%, and the MHEH has high voltage output characteristics in multiple directions. Compared with traditional multi-directional and self-adaptive energy harvesters, the MHEH utilizes a reverse-thinking method to generate continuous rotational motion of the cantilever beam, thus eliminating the influence of external excitation direction on the normal vibration of the cantilever beam. In addition, the MHEH has achieved hybrid energy harvesting with a single cantilever beam and multiple mechanisms, providing new ideas for multi-directional energy harvesting. Full article

This paper presents a comprehensive summary of recent advances in circuit topologies for piezoelectric energy harvesting, leading to self-powered systems (SPSs), covering the full-bridge rectifier (FBR) and half-bridge rectifier (HBR), AC-DC converters, and maximum power point tracking (MPPT) techniques. These approaches are analyzed with respect to their advantages, limitations, and overall impact on energy harvesting efficiency. Th work explores alternative methods that leverage phase shifting between voltage and current waveform components to enhance conversion performance. Additionally, it provides detailed insights into advanced design strategies, including adaptive power management algorithms, low-power control techniques, and complex impedance matching. The paper also addresses the fundamental principles and challenges of converting mechanical vibrations into electrical energy. Experimental results and performance metrics are reviewed, particularly in relation to hybrid approaches, load impedance, vibration frequency, and power conditioning requirements in energy harvesting systems. This review aims to provide researchers and engineers with a critical understanding of the current state of the art, key challenges, and emerging opportunities in piezoelectric energy harvesting. By examining recent developments, it offers valuable insights into optimizing interface circuit design for the development of efficient and self-sustaining piezoelectric energy harvesting systems. Full article

Efficient and low-loss harvesting methods are crucial for preserving the postharvest quality of the first crop of goji berries grown in saline–alkali soils. However, as a brittle horticultural fruit rich in diverse bioactive compounds, goji berries are highly vulnerable to mechanical damage during harvesting, which adversely affects their storability and subsequent processing. To address this challenge, a multi-degree-of-freedom vibration model was developed based on the growth characteristics of first-crop organic goji berry fruit-bearing branches in the Qinghai region. The dynamic response of the branches under various excitation conditions was simulated, and the effects of excitation position, frequency, force amplitude, and phase angle on the fruit detachment rate, impurity rate, and breakage rate were systematically analyzed. Based on both the simulation and experimental results, a response surface methodology (RSM) was employed to optimize the picking parameters. The results of the field experiment showed that under the optimal conditions of vibration excitation in the ripe fruit area, a frequency of 5.7 Hz, an amplitude of excitation force of 0.27 N, a phase angle of 135°, a fruit picking rate of 97.58%, a miscellaneous content rate of 5.12%, and a breakage rate of 7.66% could be realized. The results of this study help to maintain the postharvest quality of first-crop goji berry fruits in saline–alkali land, and also provide a theoretical basis and practical reference for the optimization of first-crop goji berry harvesting equipment. Full article

Exploring the dynamics of nonlinear nanofluidic flow-induced vibrations, this work focuses on single-walled branched carbon nanotubes (SWCNTs) operating in a thermal–magnetic environment. Carbon nanotubes (CNTs), renowned for their exceptional strength, conductivity, and flexibility, are modeled using Euler–Bernoulli beam theory alongside Eringen’s nonlocal elasticity to capture nanoscale effects for varying downstream angles. The intricate interactions between nanofluids and SWCNTs are analyzed using the Differential Transform Method (DTM) and validated through ANSYS simulations, where modal analysis reveals the vibrational characteristics of various geometries. To enhance predictive accuracy and system stability, machine learning algorithms, including XGBoost, CATBoost, Random Forest, and Artificial Neural Networks, are employed, offering a robust comparison for optimizing vibrational and thermo-magnetic performance. Key parameters such as nanotube geometry, magnetic flux density, and fluid flow dynamics are identified as critical to minimizing vibrational noise and improving structural stability. These insights advance applications in energy harvesting, biomedical devices like artificial muscles and nanosensors, and nanoscale fluid control systems. Overall, the study demonstrates the significant advantages of integrating machine learning with physics-based simulations for next-generation nanotechnology solutions. Full article