Search Results (3,735)

Road surface conditions significantly impact driving safety and maintenance costs. Especially in connected and automated vehicles (CAVs), the road surface type recognition is critical for environmental perception. Traditional road surface recognition methods face limitations in feature extraction, so an improved one-dimensional convolutional neural network (1D-CNN) algorithm was proposed based on the VGG16 architecture. A vibration signal acquisition system was developed to efficiently acquire high-quality vehicle vibration signals. The optimized 1D-CNN algorithm model contains only 101.6 k parameters, significantly reducing computational cost and training time while maintaining high accuracy. Data augmentation, Adam optimization algorithm and L2 regularization were integrated to enhance generalization capabilities and suppress overfitting. On public datasets and actual vehicles tests, recognition accuracy rate reached 99.3% and 99.4%, respectively, substantially outperforming conventional methods. The algorithm also exhibited strong adaptability to different data sources. The research findings have implications for the accurate and efficient identification of road surfaces. Full article

The dynamic load caused by vehicle vibration due to an uneven pavement surface is a primary factor affecting the structural performance and service life of asphalt pavement. As the principles of vibration mechanics, in conjunction with the coherence function of the vehicle’s left and right wheels, along with the lag between front and rear wheels, the entire vehicle vibration model for three-axle and four-axle heavy-load vehicles was developed using Simulink software. Through simulation, the root-mean-square value of the dynamic load and the dynamic load coefficient of the vehicle with different pavement roughness grades, speeds, loads, and cornering radii were analyzed. The outcomes demonstrate that a nonlinear rise in the wheel dynamic load occurs when pavement roughness increases. The greater the speed, the greater the impact of pavement roughness on the dynamic load. An increase in vehicle load tends to reduce vehicle vibrations. The interaction between vehicle vibration frequency and road excitation frequency is essential in figuring out the loads, and a negative influence on the pavement structure should be given more attention when the vehicle is driving at low speed. The dynamic load coefficient of the left and right wheels is greatly affected when the vehicle is in a lateral tilt. The findings offer valuable insights for selecting appropriate loads in pavement structure design. By constructing 11 degrees of freedom for a three-axle vehicle and 16 degrees of freedom for a four-axle heavy-duty vehicle model, the dynamic load variation law under different roughness excitation conditions is systematically analyzed. The results can be applied to the selection of vehicle load in asphalt pavement design to make it closer to the actual driving state, which will be helpful for improving accuracy in the design of pavement structure and avoiding early damage to the pavement. Full article

The rapid expansion of urban rail transit networks has raised concerns about metro-induced vibrations in over-track structures. Floor vibration isolation systems provide an adaptable and efficient mitigation strategy, offering flexibility in architectural design while enhancing vibration comfort. This study investigates the dynamic characteristics and parameter optimization of such systems under multi-point excitations. A four-degree-of-freedom (4-DOF) model is developed to analyze the dynamic behavior of the isolation floor system, revealing that the height difference between the horizontal bearing installation plane and the centroid of the isolation plate critically induces “translation–rotation” coupling. Theoretical stability analysis and finite element simulations are employed to evaluate the effects of key parameters, including the isolation plate length, number of bearings, bearing arrangement, isolation frequency, and damping ratio. The results demonstrate that increasing the number of bearings reduces floor acceleration and displacement while improving response uniformity. The optimal isolation frequency range is identified as 3–5 Hz, balancing both isolation efficacy and uniformity. Additionally, increasing the bearing damping ratio to 0.05–0.1 can comprehensively mitigate vibration responses and improve vibration uniformity. Sensitivity analysis confirms that these optimal parameters exhibit strong robustness against ±20% practical deviations, ensuring reliable performance in engineering applications. These findings provide theoretical and practical guidance for optimizing floor isolation systems in over-track buildings, contributing to the sustainable development of urban rail transit networks. Full article

In this paper, in order to effectively reduce the electromagnetic noise of automotive electronic water pumps, a Hybrid Random Carrier Space Vector Pulse Width Modulation Hybrid Random Carrier Space Vector Pulse Width Modulation, (HRCSVPWM) technique based on linear congruential generator (LCG) algorithm is proposed to study the suppression effect of current harmonics and acoustic vibration response with an automotive electronic water pump as the research object. Firstly, the HRCSVPWM based technique is proposed on the basis of SVPWM and pulse width modulation strategies. Secondly, the performance of random numbers generated for HRCSVPWM is analyzed, and it is proposed to use an LCG random number generator to generate excellent random numbers combined with a genetic algorithm to quickly determine the optimal values of three random parameters, namely, random number Ri, mixing degree coefficient Ki, and spreading width Ti, which enhances the stochasticity and spatial traversal of random sequences and ensures the effect of the HRSVPWM control method. Finally, simulation analysis is carried out, and a noise experimental platform is built for experimental verification. The results show that using the improved HRCSVPWM control strategy, compared with the SVPWM control strategy, the total harmonic content decreased by close to 21.81%, and the sound pressure level amplitude decreased by an average of approximately 6 dB. Full article

This study investigates the nonlinear dynamics and control of an underactuated hybrid system consisting of a Duffing oscillator, a pendulum, and a piezoelectric energy harvester. A novel Piezoelectric Harvester Proportional–Derivative (PHPD) control scheme is introduced, which integrates the harvester’s electrical output directly into the feedback loop to achieve simultaneous vibration suppression and energy utilization. The nonlinear governing equations are derived and analyzed using the Multiple-Scale Perturbation Technique (MSPT) to obtain reduced-order dynamics. Bifurcation analysis is employed to identify stability boundaries and critical parameter transitions, while numerical simulations based on the fourth-order Runge–Kutta method validate the analytical predictions. Furthermore, frequency response curves (FRCs) and an ideal system are evaluated under multiple controller and system parameter configurations. Bifurcation classification is performed on the analyzed figure to detect various bifurcations within the system, along with the computation of the Largest Lyapunov Exponent (LLE). The results demonstrate that PHPD control significantly reduces vibration amplitude and accelerates convergence, offering a new pathway for energy-efficient, high-performance control in nonlinear electromechanical systems. Full article

On-machine measurement is a highly effective approach for enhancing machining accuracy and efficiency. A critical factor influencing the accuracy of on-machine measurements is the straightness error of the linear guideway. However, this error is significantly affected by environmental factors such as temperature, vibration, and gravity deformation. To improve the measurement accuracy of machine tools, this study investigates the impacts of these factors on straightness errors and proposes an innovative separation and compensation model for linear guideway straightness. A thermo-mechanical coupling simulation is employed to establish a model that quantifies the influence of thermal errors on straightness. The results demonstrate that thermal gradients cause the straightness error to bend to varying degrees, depending on the temperature distribution. Furthermore, a vibration error model is developed, revealing that the vibration period is approximately twice the ball diameter. Notably, vibration errors can be effectively mitigated using a band-stop filter to eliminate the corresponding frequency components. The study also addresses the effect of gravity deformation, comparing the deformation under different support conditions, highlighting the significance of precise support positioning. Through experimental validation of the straightness error separation and compensation model, it is shown that the straightness error of a conventional linear guideway can be reduced by 95%, and the compensated straightness error is less than 0.2 μm. This novel approach not only improves the accuracy of on-machine measurement but also provides valuable insights for optimizing machine tool performance under dynamic operating conditions. Full article

The Rapidly-exploring Random Tree Star (RRT*) algorithm is widely applied in robotic manipulator path planning, yet it does not directly consider motion control, where abrupt changes may cause shocks and vibrations, reducing accuracy and stability. To overcome this limitation, this paper proposes the Kinematically Smoothed, dynamically Biased Bidirectional Potential-guided RRT* (KSBB-P-RRT*) algorithm, which unifies path planning and motion control and introduces three main innovations. First, a fast path search strategy on the basis of Bi-RRT* integrates adaptive sampling and steering to accelerate exploration and improve efficiency. Second, a triangle-inequality-based optimization reduces redundant waypoints and lowers path cost. Third, a kinematically constrained smoothing strategy adapts a Jerk-Continuous S-Curve scheme to generate smooth and executable trajectories, thereby integrating path planning with motion control. Simulations in four environments show that KSBB-P-RRT* achieves at least 30% reduction in planning time and at least 3% reduction in path cost, while also requiring fewer iterations compared with Bi-RRT*, confirming its effectiveness and suitability for complex and precision-demanding applications such as agricultural robotics. Full article

Flying-wing aircraft based on high-aspect-ratio wings are a popular configuration for many aerospace engineering applications. Cracked (or cross) control surface structures can adjust the aerodynamic characteristics of flying-wing aircraft. Deep investigations into the effects of such a control surface can provide a helpful design foundation. This paper investigates the mass distribution influences of cracked control surfaces on gust responses of high-aspect-ratio flying wings. Validated finite element modelling, revised by detailed ground vibration test (GVT) with a frequency error of less than 10%, reveals that root boundary conditions significantly affect the natural modes and frequencies of present wings with cracked control surfaces. Changes in control surface (CS) mass have a critical impact on gust response: a 150 g increase in CS mass results in a 15–22% increase in peak response acceleration and a 25–30% increase in response duration, while redistributing mass to the outboard CS reduces the peak response by 18–26% while keeping the total mass consistent. The results can provide an effective suppression strategy for the gust responses of flying-wing configurations without redesigning the main structure. Full article

Precision agriculture applies data-driven strategies to manage spatial and temporal variability within fields, aiming to increase productivity while minimizing pressure on natural resources. As interest in smart tillage systems expands, this study explores a central question: Can tillage tools be used to measure soil compaction during regular field operations? To investigate this, vibration data measurements were collected from a cultivator shank in the northeast of Kansas using the AVDAQ system. The test field soils were Reading silt loam and Eudora–Bismarck Grove silt loams. The relationship between shank vibrations, soil moisture (measured by a Hydrosense II soil–water sensor), and soil compaction (measured by a cone penetrometer) was evaluated using machine learning models. Both XGBoost and Random Forest demonstrated strong predictive performance, with Random Forest achieving a slightly higher correlation of 93.8% compared to 93.7% for XGBoost. Statistical analysis confirmed no significant difference between predicted and measured values, validating the accuracy and reliability of both models. Overall, the results demonstrate that combining vibration data with soil moisture data as model inputs enables accurate estimation of soil compaction, providing a foundation for future in situ soil sensing, reduced tillage intensity, and more sustainable cultivation practices. Full article

The detection of damage in wind turbine blades is critical for ensuring their operational efficiency and longevity. This study presents a novel method for wind turbine blade damage detection, utilizing Gramian Angular Field (GAF) transformations of vibration signals in combination with Convolutional Neural Networks (CNNs). The GAF method enables the transformation of vibration signals, which are captured using a triaxial accelerometer, into angular representations that preserve temporal dependencies and reveal distinctive texture patterns that can be associated with structural damage. This transformation facilitates the capability of CNNs to identify complex features correlated with crack severity in wind turbine blades, thereby enhancing the precision and effectiveness of turbine fault diagnosis. The GAF-CNN model achieved a notable classification accuracy over 99.9%, demonstrating its robustness and potential for automated damage detection. Unlike traditional methods, which rely on expert interpretation and are sensitive to noise, the proposed system offers a more efficient and precise tool for damage monitoring. The findings suggest that this method can significantly enhance wind turbine condition monitoring systems, offering reduced dependency on manual inspections and improving early detection capabilities. Full article

Chatter vibration in machining operations has been identified as one of the major obstacles to improving surface quality and productivity. Therefore, efficiently and accurately predicting stable cutting regions is becoming increasingly important, especially in high-speed milling processes. In this study, on the basis of a predictor–corrector scheme, the following three error correction methods are developed for milling stability analysis: the Correction Hamming–Milne-based method (CHM), the Correction Adams–Milne-based method (CAM) and the Predictor–Corrector Hamming–Adams–Milne-based method (PCHAM). Firstly, we employ the periodic delay differential equations (DDEs), which are usually adopted to describe mathematical models of milling dynamics, and the time period of the coefficient matrix is divided into two unequal subintervals based on an analysis of the vibration modes. Then, the Hamming method and the fourth-order implicit Adams–Moulton method are separately utilized to predict the state term, and the Milne method is adopted to correct the state term. Based on local truncation error, combining the Hamming and Milne methods creates a CHM that can more precisely approximate the state term. Similarly, combining the fourth-order implicit Adams–Moulton method and the Milne method creates a CAM that can more accurately approximate the state term. More importantly, the CHM and the CAM are employed together to acquire the state transition matrix. Thereafter, the effectiveness and applicability of the three error correction methods are verified by comparing them with three existing methods. The results demonstrate that the three error correction methods achieve higher prediction accuracy without sacrificing computational efficiency. Compared with the 2nd SDM, the calculation times of the CHM, CAM and PCHAM are reduced by around 56%, 56% and 58%, respectively. Finally, verification experiments are carried out using a CNC machine (EMV650) to further validate the reliability of the proposed methods, where ten groups of cutting tests illustrate that the stability lobes predicted by the three error correction methods exhibit better agreement with the experimental results. Full article

This paper investigates the nonlinear dynamics of the wheel-side planetary reducer, considering the tooth wear effect. The tooth wear model based on the Archard adhesion wear theory is established, and the impact of tooth wear on meshing stiffness and piecewise-linear backlash of the planetary gear system is discussed. Then, the torsional vibration model and dimensionless differential equations considering tooth wear for the wheel-side planetary reducer are established, in which meshing excitations include time-varying mesh stiffness (TVMS), piecewise-linear backlash, and transmission error. The dynamic responses are numerically solved using the fourth-order Runge–Kutta method. On this basis, the nonlinear dynamics, such as the bifurcation and chaos properties of the wheel-side planetary reducer with tooth wear, are analyzed. Simulation results demonstrate that the existence of tooth wear reduces meshing stiffness and increases backlash. The reduction in the meshing stiffness changes the bifurcation path and chaotic amplitude of the system, inducing chaotic phenomena more easily. The increase in the gear backlash causes a higher amplitude of the relative displacement and more severe vibration. Full article

The active or adjustable journal bearings are designed with unique mechanisms to reduce the rotor-bearing system lateral vibrations by adjusting their damping and stiffness. The article provides a comprehensive review of the literature, outlining the structure and findings of studies on active bearings. Over the years, various kinds of adjustable bearing designs have been developed with unique operational mechanisms. Such bearing designs include adjustable pad sectors, externally adjustable pads, active oil injection through pad openings, and flexible deformable sleeves. These modifications enhance the turbine shaft line’s performance by increasing the system’s overall stability. The detailed review in this paper highlights the characteristics of bearings, along with the key advantages, limitations, and potential offered by active control across different bearing types. The efficiency of any rotor system can be greatly enhanced by optimally selecting the adjustable bearing parameters. These adjustable bearings have demonstrated a unique capability to modify the hydrodynamic operation within the bearing clearances. Experimental studies and simulation approaches were also utilized to optimize bearing geometries, lubrication regimes, and control mechanisms. The use of advanced controllers like PID, LQG, and Deep Q networks further refined the stability. The concluding section of the article explores potential avenues for the future development of active bearings. Full article

Elevated railways are a crucial component of railway lines, characterized by their widespread distribution, simple structure, and low cost, while actively promoting local economic development. However, they also cause significant ground vibrations when trains pass. Similarly, considerable vibration levels are transmitted to the subgrade and surrounding structures when trains operate on viaducts within the Loess Plateau region. However, research on mitigating these vibration effects remains relatively scarce. This study focused on the impacts of such vibrations on surrounding buildings and stratum structures and evaluated the effectiveness of a vibration isolation trench in mitigating these effects. Time frequency domain analysis of ground vibrations during train passage revealed that the characteristic frequency of the train-induced pulse excitation in the track structure had a pronounced peak in the spectrum curve. The introduction of a vibration isolation trench effectively blocked the propagation of vibration waves in the soil, reduced soil vibration, and significantly lowered the peak value in the spectrum. Numerical simulations were employed to analyze the elliptical polarization dispersion characteristics of surface wave propagation with the vibration isolation trench in place, confirming the effective damping performance of the trench. These findings could offer a valuable reference for high-speed railway vibration isolation and significantly advance the application of surface wave theory in high-speed railway technology. Full article

Structure and nonlinear spectra of the basal surface of ice Ih were investigated by molecular dynamics simulations. At a temperature significantly lower than the melting temperature $T_m$, the ice structure at the interface is only weakly perturbed by the presence of surface. The computed nonlinear spectrum of the interface well agrees with the experimental data and the results of the calculations provide the molecular-level interpretation of spectral features. In particular, the ice surface specific positive peaks in the Im[${\chi }^{\left(2\right)}$] spectrum at ∼3180 cm⁻¹ and at ∼3420 cm⁻¹ were found to result from the low- and high-frequency vibrational modes of quadruply H-bonded surface molecules, respectively. The spectrum of the crystalline ice interface is significantly affected by intermolecular interactions. Upon increasing the temperature, the structural disorder extends to the second water bilayer. The thickness of the premelted water layer of 6–8 Å can be estimated at the temperature by ca. 5 K below $T_m$. The increase in the temperature results in a change in the intensity and shape of the nonlinear spectrum of the ice Ih interface. The changes can be explained by the interconversion between different H-bonded surface species and by an increase in disordering of water molecules that reduces strength of intermolecular interactions. Results of the present work contribute to our understanding of the structure–spectrum relationship of the ice/air interface, and shed light on the origins of features in the nonlinear spectra of the system. Full article