Search Results (291)

During field operations, the potato harvester is subjected to multiple sources of excitation, including internal vibratory mechanisms and field surface excitation, resulting in significant vibrations in the frame. Based on the physical parameters of the harvester’s internal structure and the connection parameters between components, a 12-degree-of-freedom (12-DOF) dynamic model of the entire machine was constructed. The corresponding simulation model was created in a MATLAB/Simulink environment to analyze the vibration characteristics of each component during harvesting operations. The comparison between actual and simulated signals shows that the RMS error of acceleration is only 2.42%, indicating that introducing two degrees of freedom in pitch and roll directions to the potato harvester can accurately describe its vibration characteristics. On this basis, the Bayesian optimization algorithm was used to obtain optimal connection parameters. The optimization results demonstrate a 0.85 m/s² and 0.45 m/s² increase in RMS values for the soil-cutting disc and lifting chain, respectively, effectively enhancing the harvester’s work efficiency, while the frame exhibited a 0.31 m/s² reduction in RMS value, significantly improving structural stability. This study provides a theoretical foundation for the parameter optimization of large-scale agricultural machinery. Full article

Ultra-high-power wind turbine generator bearings are susceptible to micro-spalling and electrical erosion in long-cycle operation, which seriously affects the operating efficiency and service life of the unit. For this reason, this paper adopts a kind of composite grease containing nano-hydroxy magnesium silicate powder and, through the wind turbine assembly machine test and raceway surface analysis, systematically investigates its impact on bearing temperature rise, bearing vibration, and wind turbine power under actual working conditions to meet the lubrication requirements of wind turbine generator bearings. The results of the study showed that the composite grease significantly reduced the operating temperature of the wind turbine bearings under full operating conditions. It is worth noting that the reduction in generator bearing temperature varied among the three turbines due to uncertain environmental factors. In addition, the grease effectively increased the output power of the turbine under medium wind speed loading conditions, further verifying its potential value and practical effect in the application of wind turbines. Full article

This literature review focuses on titanium alloys, which are crucial in modern manufacturing due to their excellent properties. The review covers their classification, machining challenges, and advanced cutting methods. Different alloy types (α-Ti, β-Ti, and α+β-Ti) have distinct characteristics and applications; their machining challenges include low thermal conductivity and pronounced chemical reactivity. Nowadays, advanced cutting methods of titanium alloys involve innovated tool design, efficient coolant techniques, and ultrasonic vibration cutting. The impact of these methods on cost, quality, and efficiency is analyzed, considering both positive and negative aspects. Lastly, strategies for cost reduction, efficiency improvement, and quality enhancement are explored, highlighting the complex relationship between these factors in titanium alloy processing. Full article

The adjustment of delay time in open-pit bench blasting is a research hotspot in vibration control. Its core lies in utilizing the periodic characteristics of vibration waves to achieve the superposition and cancellation of wave peaks and troughs. However, due to the spatiotemporal variability in the propagation of blast-induced vibration waves, the optimal delay time determined for vibration control requirements at a specific protected area (monitoring point) makes it difficult to achieve the misalignment superposition effect simultaneously at multiple monitoring points. To address the challenge of multi-area vibration control in open-pit bench blasting, this paper proposes an adjustment method based on local delay adjustment. First, a spatiotemporal relationship model between blast holes with monitoring points is established to calculate vibration wave arrival times. This enables rapid hole identification during dense wave arrivals at monitoring points, with waveform separation achieved through initiation delay adjustments. Following the Anderson principle, reconstructed single-hole vibrations are superimposed according to the wave arrival sequence to validate control efficacy. Statistical analysis of concurrent wave arrivals across all-direction monitoring points identifies high-probability vibration hazard locations. Targeted delay adjustments for blast holes within clustering arrival periods at these locations enable comprehensive vibration reduction. Field data confirm that single-point control reduces peak vibration by >10.55% through simultaneously reducing the amount of waves in clustering arrival periods. Multi-point control resolves seven hazard locations across two directions, attaining 88.57% hazard elimination efficiency and 14.05% peak velocity attenuation. This method achieves vibration control through local delay adjustments while maintaining the fragmentation effect of the original scheme, providing a new approach to solving the challenge of vibration control in large-scale blasting areas. Full article

GIS circuit breakers play a critical role in maintaining the reliability of modern power systems. However, mechanical failures, such as spring fatigue, transmission rod jamming, and loosening of structural components, can significantly impact their performance. Traditional diagnostic methods struggle to identify these issues effectively due to the enclosed nature of GIS equipment. This study explores the use of vibration signal analysis, specifically during the closing transient phase of the GIS circuit breaker. The proposed method combines wavelet packet decomposition, rough set theory for feature extraction and dimensionality reduction, and the S_Kohonen neural network for fault type identification. Experimental results demonstrate the robustness and accuracy of the method, achieving a diagnostic accuracy of 96.7% in identifying mechanical faults. Compared with traditional methods, this approach offers improved efficiency and accuracy in diagnosing GIS circuit breaker faults. The proposed method is highly applicable for predictive maintenance and fault diagnosis in power grid systems, contributing to enhanced operational safety and reliability. Full article

Nowadays, it is very important to reduce structural vibrations and control seismic reactions against earthquakes. Nonlinear viscous dampers are known as one of the effective tools for absorbing and dissipating earthquake energy to reduce structural responses. The characteristics of nonlinear viscous dampers, including the damping coefficient, axial stiffness, and velocity exponent, play a crucial role in their performance. In this research, the optimization of nonlinear viscous damper characteristics to minimize the peak absolute displacement of the roof in three- and five-story reinforced concrete flexural frames under the El Centro earthquake record has been investigated. Structural modeling and dynamic analyses are performed using OpenSees 3.5.0 software, and damper parameter optimization is performed through a new combination of two marine predator algorithms (MPA) and particle swarm optimization (PSO). Furthermore, the performance of the new algorithm is compared with each of these methods separately to evaluate the efficiency improvement for displacement reduction. The results show that the hybrid algorithm has demonstrated significant performance improvement compared to the independent methods in identifying optimal values. Specifically, in the three-story frame, the roof displacement using the MPA-PSO method was 0.77026, which is lower than 0.77140 with the PSO method. Additionally, the damping coefficient in this method decreased to 14.22824 kN·s/mm, which is a significant reduction compared to 19.32417 kN·s/mm in the PSO method. Furthermore, in the more complex five-story frame, the two comparison methods were unable to reach the optimal solution, while the proposed method successfully found an optimal solution. These results validate the performance and advantages of the proposed hybrid algorithm. Full article

Grade 14.9 superhigh-strength bolts (SHTBs) are a type of high-strength steel bolt with a nominal tensile strength of 1400 MPa, which is significantly higher than the commonly used Grade 10.9 high-strength bolt (HSB), which has a nominal tensile strength of 1000 MPa. The use of an SHTB can reduce the number of bolts required in connections or joints, leading to material savings and improved construction efficiency. However, like HSB, the mechanical properties of an SHTB can be significantly degraded at high temperatures, though the extent of this reduction may differ. In this study, the authors designed and conducted experiments on SHTBs under elevated temperatures including both vibration and tensile coupon tests. Based on the test data, the stress–strain curves and key mechanical properties such as the Young’s modulus, yield stress, ultimate stress, ultimate strain, percentage elongation, cross-sectional area reduction, and failure strain were obtained and analyzed for various high-temperature conditions. Furthermore, a new three-stage model was proposed to describe the stress–strain relationship of SHTBs under fire conditions. Additionally, empirical formulae were developed to predict the mechanical properties of SHTBs under elevated temperatures, providing valuable insights for engineering applications and fire safety design. Full article

Experimental modal analysis has proven effective in damage identification of civil structures but has not been extensively applied to multi-leaf masonry structures, particularly in the context of wall tie inspection. This paper investigates the applicability of non-destructive, vibration-based damage identification methods to a one-storey masonry veneer wall to detect wall tie deterioration based on changes in modal parameters. An impact hammer was used to collect vibration data from eight different wall tie deterioration test cases by disconnecting the wall ties at various locations. The downshift of natural frequencies was recorded for all deterioration test cases, and a reduction of up to 38% was observed when the top row of wall ties was disconnected, highlighting the importance of wall ties to the overall stiffness of the masonry veneer wall system. In terms of damage localisation accuracy, the parameter-based method performed the best by successfully identifying seven out of eight damaged scenarios without additional noise. The findings show that the detection of wall tie deterioration using non-destructive, vibration-based damage identification methods is viable, providing an alternative wall tie inspection method with significant benefits to infrastructure management, thereby enhancing safety, efficiency, and sustainability in maintaining and preserving masonry veneer walls. Full article

This study examines the efficacy of a seat inertial suspension system in relation to vibration isolation and energy recovery in electric commercial vehicles. The research focuses on the structural modifications of the suspension system that arise from the incorporation of an inerter, a novel vibration isolation component. A dynamic model of the seat inertial suspension is constructed, which includes two different structures consisting of components connected in parallel and in series. The analysis explores how the absorption of suspension parameters affects both seat comfort and the characteristics of energy harvesting. Furthermore, an optimal design methodology for the seat inertial suspension is proposed, seat comfort and energy recovery efficiency are also taken into consideration. The findings reveal that the parallel-structured seat inertial suspension system demonstrates superior overall performance. Specifically, it achieves a 36.6% reduction in seat acceleration, a 55.3% decrease in suspension working space, and an energy harvesting efficiency of 41.9%. The seat inertial suspension significantly improves occupant comfort by reducing seat acceleration, significantly reducing the amplitude of seat suspension movement, and recovering most of the seat suspension’s vibration energy, in comparison to traditional seat suspension systems. Full article

In modern agriculture, reducing the internal moisture content of crop seeds is essential to enhance the activity and mobility of seed oil molecules, thereby increasing oil yield while minimizing the risk of mold and deterioration. However, traditional drying methods often result in uneven heating, leading to seed scorching and diminished drying efficiency and economic returns. To address these limitations, this study proposes a novel thin-layer seed drying system incorporating a redesigned drying tray structure. Specifically, the system places the seed-bearing tray beneath a vibration module operating at a predetermined frequency. The vibration mechanism induces the uniform motion of the seeds, thereby preventing localized overheating (scalding) and enabling automatic weighing for the real-time monitoring of moisture reduction during the drying process. The advancement of wireless sensor technologies in agriculture has enabled the deployment of more refined, large-scale monitoring networks. In this work, a commercial chip-based piezoelectric vibration detection device was integrated into the experimental setup to collect time-domain response signals resulting from interactions among seeds, impurities, and the drying tray. These signals were used to construct a comprehensive database of seed collision signatures. To mitigate discontinuities in signal transmission caused by vibration and potential equipment failure, the shortest routing protocol (SRP) was implemented. Additionally, the system outage probability (OP) and a refined closed-form solution for signal transmission reliability were derived under a Rayleigh fading channel model. To validate the proposed method, a series of experiments were conducted to determine the optimal vibration frequencies for various seed types. The results demonstrated a reduction in seed scalding rate to 1.5%, a decrease in seed loss rate to 0.4%, and an increase in moisture monitoring accuracy to 97.0%. Compared to traditional drying approaches, the vibrating drying tray substantially reduced seed loss and effectively distinguished between seeds and impurities. Furthermore, the approach shows strong potential for broader applications in seed classification and moisture detection across different crop types. Full article

Traditional design and shaping methods of helical gears may have difficulties in meeting the requirements of multiple performance indicators simultaneously, such as tooth surface accuracy, load-carrying capacity, and transmission efficiency. This study attempts to overcome these limitations through a multi-objective optimization method and achieve the comprehensive optimization of multiple performance indicators. This paper aims to boost gear system power transmission and cut vibration and noise. It assesses gear shaping impacts via normal load per unit length of the helical gear surface and gear vibration amplitude. Traditional gear shaping schemes were first determined using classic theories and formulas. Then, an improved genetic algorithm was applied to seek optimal helical gear shaping parameters. An eight-degree-of-freedom lumped mass model of the helical gear transmission system, considering bending–torsion–axial coupling, was developed based on Newton’s second law and solved via the fourth-order Runge–Kutta method. Comparisons showed that the traditional shaping scheme reduced the maximum normal load per unit length by 20.6% and the system’s vibration amplitude by 18.3%. In contrast, the improved genetic algorithm achieved greater reductions of 26.34% and 27.2%, respectively. Both methods effectively decreased the maximum normal load per unit length and system vibration amplitude, with the improved genetic algorithm yielding superior results. This work offers a key theoretical basis and reference for enhancing load transmission, reducing costs, and mitigating vibration and noise in gear transmission systems. Full article

Co-based amorphous wires (Co-AWs) are functional materials renowned for their high impedance change rate in magnetic fields and a pronounced giant magnetoimpedance (GMI) effect. In this study, magnetron sputtering (MS) and dip-coating (DC) techniques were employed to fabricate carbon-based nanocoatings aimed at modulating the GMI properties of Co-AWs. The magnetic properties and GMI responses of the composite Co-AWs with carbon-based coatings were comparatively analyzed. The results demonstrate that both methods effectively enhanced the GMI properties of the coated Co-AWs. The DC method emerged as a rapid and efficient approach for forming the coated film, achieving a modest enhancement in GMI performance (10% enhancement). In contrast, the MS technique proved more effective in improving the GMI effect, yielding superior results. Co-AWs coated via Ms exhibited smoother surfaces and reduced coercivity. Notably, the GMI effect increased with the thickness of the sputtered carbon coatings, reaching a maximum GMI effect of 522% (a remarkable 357% enhancement) and a sensitivity of 33.8%/Oe at a coating thickness of 334 nm. The observed trend in the GMI effect with carbon layer thickness corresponded closely to variations in transverse permeability, as determined by vibrating sample magnetometry (VSM). Furthermore, the carbon coating induced changes in the initial quenching stress on the surface of the Co-AWs, leading to alterations in impedance and a significant reduction in the characteristic frequency of the Co-AWs. Our findings provide valuable insights into the modulation of GMI properties in Co-AWs, paving the way for their optimized application in advanced magnetic sensor technologies. Full article

The bed expansion height serves as a macroscopic representation of the efficiency with which vibrational energy is transmitted within pulsed fluidized beds. Due to its complex nonlinear characteristics, further research is needed to explore the fluidization mechanisms in pulsed fluidized beds and identify effective predictive models for expansion ratios. This work evaluates and analyzes the predictive capabilities of models established based on theoretical learning, as well as three machine learning methods. Additionally, dimensionless numbers are introduced to facilitate dimensionality reduction. Among these methods, the extreme gradient boosting model demonstrated exceptional performance, achieving an R² value of 0.9907 on the training set and reaching 0.9300 on the testing set. Furthermore, an interpretability analysis of the extreme gradient boosting model was conducted using Shapley additive explanations, revealing that f/f_n is the most significant factor influencing the bed expansion ratio, while H₀/D has a relatively minor effect. These findings provide a basis for effectively predicting bed expansion ratios and facilitate further scale-up studies in pulsed fluidized beds. Full article

The maglev gyroscope torque feedback orientation measurement system, equipped with abundant sampling data and high directional accuracy, plays a crucial role in underground engineering construction. However, when subjected to external instantaneous vibration interference, the gyroscope rotor signal frequently exhibits abnormal jumps, leading to significant errors in azimuth measurement results. To solve this problem, we propose a novel noise reduction algorithm that integrates Moving Average Filtering with Autoregressive Integrated Moving Average (MAF-ARIMA), based on the noise characteristics of the rotor jump signal. This algorithm initially adaptively decomposes the rotor signal, subsequently extracting the effective components of the north-seeking torque with precision and applying MAF processing to effectively filter out noise interference. Furthermore, we utilize the stable sampling trend data of the rotor signal as sample data, employing the ARIMA model to accurately predict the missing abnormal jump trend data, thereby ensuring the completeness and coherence of the rotor signal trend information. Experimental results demonstrate that, compared to the original rotor signal, the reconstructed signal processed by the MAF-ARIMA algorithm exhibits an average reduction of 70.58% in standard deviation and an average decrease of 47.31% in the absolute error of azimuth measurement results. These findings fully underscore the high efficiency and stability of the MAF-ARIMA algorithm in processing gyroscope rotor jump signals. Full article

The integration of Finite Element Method (FEM) simulations with laser-based techniques has significantly advanced acoustic research by enhancing wave measurement, analysis, and prediction in complex solid media. This review examines the role of the FEM in laser-based acoustics for wave propagation, defect detection, biomedical diagnostics, and engineering applications. FEM models simulate ultrasonic wave generation and propagation in single-layer and multilayered structures, while laser-based experimental techniques provide high-resolution validation, improving modeling accuracy. The synergy between laser-generated ultrasonic waves and FEM simulations enhances defect detection and material integrity assessment, making them invaluable for non-destructive evaluation. In biomedical applications, the FEM aids in tissue characterization and disease detection, while in engineering, its integration with laser-based methods contributes to noise reduction and vibration control. Furthermore, this review provides a comprehensive synthesis of FEM simulations and experimental validation while also highlighting the emerging role of artificial intelligence and machine learning in optimizing FEM models and improving computational efficiency, which has not been addressed in previous studies. Key advancements, challenges, and future research directions in laser-based acoustic applications are discussed. Full article