Jaw Functional Orthopedics and Cranoficial Growth
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Study on the impact of wheel roundness defects on axle fatigue damage
No full textWith the continuous increase in the operating mileage of China’s high-speed railway network, wheel out-of-roundness has become increasingly common in electric multiple unit (EMU) vehicles. Wheel out-of-roundness directly increases the vibration level of the axle, affects various vehicle components, and in severe cases, may lead to fatigue fracture of the axle – a key load-bearing component – thereby causing major safety incidents. To investigate the influence of wheel out-of-roundness on axle dynamic stress and to evaluate the fatigue strength of the axle under such conditions, this study analyzes the effects of different wheel flat lengths, polygon orders and depths, as well as various operating speeds on the dynamic stress of EMU axles. Based on numerical simulation results, the fatigue damage of the axle under wheel out-of-round conditions and the impact of wheel polygonal wear over one development cycle are calculated. The findings show that within a single re-profiling cycle, wheel flats shorter than 50 mm have a negligible effect on axle fatigue damage. Furthermore, a reference limit for polygonal wear depth is proposed, providing theoretical guidance for wheel maintenance and safety assessment of EMU vehicles
MIMO radar river flow measurement based on space-velocity-time algorithm and adaptive correction model
No full textAccurate measurement of river hydrological characteristics is critical for assessing the impacts of flooding caused by meteorological and geomorphological factors. Flow velocity are key indicators in hydrological monitoring. Traditional measurement approaches, such as continuous-wave Doppler radar and pulsed radar systems, are typically mounted on bridges or fixed supports and offer only single-point measurements. These methods often suffer from limited detection range, low accuracy, and poor resistance to environmental interference. To address these limitations, this study proposes a three-dimensional flow detection framework based on multi-input multi-output (MIMO) radar sensors. By leveraging the high reliability and interference resistance of MIMO radar, along with a Space-Velocity-Time (SVT) algorithm that incorporates spatiotemporal information (two-dimensional surface velocity and time), the proposed method enables robust 3D river flow monitoring. In this study, comparative experiments were conducted on four rivers in China with different flow conditions, geomorphic features and weather environments. Results demonstrate that the proposed method achieves a measurement error of less than 5 % compared to acoustic Doppler current profilers (ADCP) and other conventional mechanical approaches, while also offering improved safety and real-time performance. Moreover, an adaptive flow correction algorithm is presented, which uses three optimized prediction models to compute the correction factor and reduces the mean streamflow measurement error to 0.79 % after correction, providing an effective solution for river gauging, flood control and flood resilience
Experimental study on vibration isolation performance of mining dump truck suspensions for improving ride comfort
No full textThis study addresses the challenge of reducing the transmission of low-frequency road excitation vibrations to the cab of mining dump trucks to enhance ride comfort. Given the harsh working conditions of these vehicles, a novel methodology combining experimental data collection and advanced signal processing techniques was developed. The research established a comprehensive vibration testing program aligned with earth-moving machinery standards, collecting vibration acceleration data under both idling and full-load operation at 35 km/h. To improve data accuracy, Singular Value Decomposition (SVD) was employed to denoise the experimental vibration data, effectively mitigating environmental interference. Subsequent Fourier transform analysis revealed the vibration energy transfer patterns of the vehicle suspension system in the frequency domain. The results indicated a significant vibration isolation rate of 89 % for the frame suspension system, contrasting with only 7 % for the cab suspension system. Notably, the cab seat suspension system was found to amplify low-frequency road excitations. Compared to previous methods, this study innovatively integrates SVD and Fourier transform techniques to provide a more accurate and detailed understanding of vibration transmission. The key result of achieving an 89 % vibration isolation rate for the frame suspension system demonstrates the effectiveness of the proposed methodology. This study offers practical optimization directions for improving suspension system performance and ride comfort in mining dump trucks, outperforming traditional approaches by providing a more comprehensive analysis and actionable insights for vibration isolation. The findings also serve as valuable references for addressing similar engineering challenges in heavy machinery
A multi-scale convolutional Siamese network for few-shot fault diagnosis of unmanned aerial vehicle rotor
No full textUnmanned Aerial Vehicles (UAVs) often face infrequent fault occurrences and high manual annotation costs, resulting in a critical shortage of valid fault samples for diagnostic research. Traditional fault diagnosis methods struggle with small sample sizes. This paper proposes a novel deep metric learning method, the Multi-Scale Convolutional Siamese Network (MSCSN), to address the few-shot learning problem in UAV rotor fault diagnosis. First, discrete wavelet transform (DWT) is used to compress and normalize the vibration signals, enhancing the prominence of signal features. Then, based on the multi-scale convolutional neural network (MS-CNN) model, the network automatically extracts multi-level features from rotor fault vibration signals, improving its adaptability to complex data. Finally, the Siamese network structure, with shared parameters and identical architecture, processes sample pairs and incorporates a small number of support samples for few-shot learning. Experimental results show that the proposed model achieves a highest accuracy of 94.42 % in few-shot tasks. In cross-domain transfer learning tests, the model achieves an average accuracy of 90.28 %, demonstrating its superior generalization ability and robustness across different environments. We also validated the model's stability using the publicly available MVS-UAV-BF dataset
Active fuzzy control of a suspension vehicle on wet and dry roads
No full textThis paper presents a co-simulation of MATLAB and CarSim to control and model a vehicle suspension system under different road surface conditions, either wet or dry, using an active fuzzy controller in MATLAB. CarSim is a professional vehicle simulation software capable of modeling nonlinear car dynamics with various uncertainties. These uncertainties are addressed by the fuzzy set approach due to its qualitative and robust control capabilities, effectively handling noise, disturbances (such as road conditions), and unknown parameters in CarSim’s vehicle model. The design of an active steering controller and rotational torque system using a fuzzy controller is crucial for enhancing road safety, especially given the increasing number of vehicle crashes. The research methodology varies based on the study's purpose, nature, and implementation capabilities. Accordingly, this research focuses on designing an integrated controller for an active four-wheel-drive system and direct rotary torque control using a fuzzy control method in the MATLAB Simulink environment. This study is analytical and functional, utilizing CarSim for simulation. A fuzzy logic-based integrated control system was designed for steady-state control to improve vehicle stability and steering. The controller adjusts the steering angle and torque to regulate the vehicle’s angular velocity and slip angle under various conditions. As tire performance changes during different maneuvers, the controller dynamically adapts its output to maintain optimal operation within the effective performance range. The significance of using fuzzy logic lies in its ability to handle non-linearity without requiring approximation, ensuring high accuracy. Additionally, it delivers excellent results in enhancing vehicle stability. The findings indicate that the controller significantly improves the vehicle’s dynamic behavior across different driving maneuvers compared to an uncontrolled vehicle
Analysis on the influence of blade pitch angle on dynamic characteristics of the rotor system
No full textAt present, few studies focus on variable-pitch fans for small-to-medium turbofan engines, with most relying on hydraulic actuation that fails to meet strict environmental and efficiency demands. This paper analyzes an electrically actuated lead-screw servo-motor-driven variable-pitch fan rotor: at 1×10⁷ N/m support stiffness, the first critical speed exceeds the operational range and pitch angle’s influence is negligible, peak unbalance response is 1.22×10⁻⁶ m linearly decreasing with pitch angle, and vibration analysis avoids resonance. Results confirm the electric pitch-change concept’s feasibility
Stodola-Vianello iteration method for the free flexural vibration frequencies of Shimpi’s single variable shear deformable beams
Get PDFThe natural vibration frequency analysis of beams is vital for their design against resonance failures because such failures occur when the excitation load frequencies of vibration coincide with such natural frequencies. This work presents a single variable shear deformable beam equation formulated using Shimpi’s displacement field assumptions. This results in a quadratic shear stress profile over the depth and a satisfaction of the transverse shear stress-free boundary conditions. The governing equation is obtained using a first principles consideration and equilibrium method as a partial differential equation (PDE) which is non-homogenous for forced vibrations and homogeneous for free vibrations. The study then used the Stodola-Vianello iteration method to solve the resulting homogeneous PDE for simply supported boundary conditions and harmonic response. The problem reduced to an iterative problem of algebra involving the computation of an (n+1)th vibratory modal shape function from an nth shape function that satisfies the boundary conditions. This work used a sinusoidal shape function which is exact for the simply supported boundary condition investigated. The use of boundary conditions solved the integration constants involved. Application of the convergence rule led to the eigenequation from which the eigenvalues were found. The eigenvalues were presented for the first four modes of vibration and for a rectangular beam. It was found that for l/h varying from 5 to 100, the natural vibration frequencies were identical with the ωn values obtained using Navier method for other thick beam vibration problems. It was also found that ωnwas close to the exact values for all vibration modes and for all values of l/h between 5 and 100. For all vibration modes and all considered l/h values negligible differences, were observed between the ωn obtained using SVIM and the exact values obtained by previous researchers
Aeroelastic stability analysis and optimal PID control strategy simulation for large-scale HAWT blades
Get PDFAiming at the classical flutter problem of wind turbine blades, a wind turbine blade aeroelastic model is constructed based on the typical leaf cross-section model of spring-mass-damper and the classical flutter aerodynamic model. The stability analysis of the wind turbine aeroelastic model is carried out using the Liapunov indirect method, and the effects of different parameters on stability are compared. Combining the aeroelastic model with the second-order model of pitch exciter, the pitch aeroelastic equation of the system is given, and the system controllability is analyzed. The optimal PID pitch control is designed, and the Simulink simulation is performed to explore the optimal combination under different combinations by selecting the torsion angle and waving displacement as the error signals, and different combinations of the torsion angle, waving displacement, and pitch angle as the optimal control objectives, respectively. The simulation results show that when the torsional angle is used as the error feedback signal and the torsional angle is set as the optimal control objective, it is the only scenario without overshoot. The overshoot in other cases ranges from 30 % to 500 %. In terms of adjustment time, this scenario also demonstrates good performance. Although it is not the fastest, the gap from the fastest is no more than 20 %. Therefore, using the torsional angle as the error feedback signal and the torsional angle as the optimal control objective is the best choice
Fault diagnosis of time-varying speed gearbox based on gated recurrent dropout attention unit
Get PDFIn response to the difficulty of fault diagnosis of gearbox under time-varying speed conditions, this paper presents a novel approach for diagnosing gearbox faults in time-varying speed, utilizing an improved gate recurrent unit (GRU), which adds attention gate mechanism and cyclic dropout learning strategies on the basis of the GRU, and constructs a new model named as gated recurrent dropout attention unit (GRDAU). By introducing attention gate mechanism to realize allocating weights dynamically, focusing on key features, and enhancing GRU’s ability to capture important information. In addition, the designed cyclic dropout learning strategy reduces excessive dependence on specific hidden states by randomly discarding some hidden state information. Finally, the robustness and excellent interference suppression ability of the proposed method were verified through case analysis of a gearbox under time-varying speed, and the diagnostic accuracy of the method is as high as 99.78 %. Comparative experiments were conducted to validate its superior performance and stronger generalization ability compared to existing advanced diagnostic methods
Design and simulation verification of differential spiral bevel gear transmission based on baja off-road vehicle
No full textThe differential spiral bevel gear of Baja off-road vehicle is designed and verified. Based on the competition rules and vehicle transmission parameters, the key geometric parameters of the gear pair are determined, and the three-dimensional model and finite element analysis software are established by UG for static contact analysis and modal analysis. The results show that the maximum contact stress of the tooth surface is 411.4 MPa, and the natural frequency of the gear pair is much higher than the excitation frequency of the system, which can effectively avoid the resonance risk. Through analysis and verification, it meets its application conditions