Search Results (33)

The deep learning architecture YOLO (You Only Look Once) has demonstrated its superior visual detection performance in various computer vision tasks and has been widely applied in the field of automatic surface defect detection. In this paper, we propose a lightweight YOLOv8-based method for the quality inspection of car body welding spots. We developed a TA-YOLOv8 network structure which has an improved Task-Aligned (TA) head detection, designed to handle a small sample size, imbalanced positive and negative samples, and high-noise characteristics of Body-in-White welding spot data. By learning with fewer parameters, the model achieves more efficient and accurate classification. Additionally, our algorithm framework can perform anomaly segmentation and classification on our open-world raw datasets obtained from actual production environments. The experimental results show that the lightweight module improves the processing speed by an average of 2.8%, with increases in detection the mAP@50-95 and recall rate of 1.35% and 0.1226, respectively. Full article

The bogie frame, as one of the most critical load-bearing structures of the Electric Multiple Unit (EMU), is responsible for bearing and transmitting various loads from the car body, wheelsets, and its own installation components. With the increasing operating speed of high-speed EMUs, especially when the design and operational speeds exceed 400 km/h, the applicability of current international standards is uncertain. The load spectrum serves as the foundation for structural reliability design and fatigue evaluation. In this paper, the measured loads of the bogie frame of a CR400AF high-speed train on the Beijing–Shanghai high-speed railway are obtained, and the time-domain characteristic of the measured loads is analyzed under different operating conditions. Then, through the Weibull distribution of three parameters, the Weibull parameters at the 450 km/h speed level are fitted, and the maximum load and cumulative frequency under the speed level are derived. Finally, the load spectrum of the bogie frame at the 450 km/h speed level is established, which provides a more realistic load condition for accurately evaluating the fatigue strength of bogie frames at higher speed levels. Full article

Despite the rapid development of vehicle intelligent technology, the aerodynamic noise problem of internal combustion engine vehicles and pure electric vehicles at high speed has always been a growing problem. In this study, the effects of the car body fender shape on the aerodynamic noises of the rearview mirror and wheel region were investigated, and a noise reduction method was also proposed by optimizing the fender shape. To realize the parametric modeling of the fender, five positional variables were selected to define the fender configuration; the free-form deformation (FFD) method was used to establish the response fender model according the DOE schemes, and computational fluid dynamics (CFD) simulations are used to obtain the noise results. Then, with the help of the radial basis function (RBF) model and the adaptive simulated annealing (ASA) algorithm, the aerodynamic shape of the fender was optimized to reduce aerodynamic noise. Comparative analysis was then employed to assess flow field characteristics of the optimized model against the original model and elucidate the fender configuration’s contribution to aerodynamic noise reduction and its realization mechanism. Full article

The rail vehicle industry wants to produce vehicles with higher speeds, to maintain and increase its market share. However, when the speed of the vehicle increases, it may have an undesirable effect on ride comfort, in terms of ride dynamics. Recent developments towards lighter and faster vehicles make the problem of ride comfort at higher speeds increasingly important. Focusing on the behavior of flexible rather than rigid body behavior should not be neglected when designing long and light car bodies. There are several approaches to incorporate body flexibility in multibody simulations and they have some superiorities and weaknesses. In this study, an efficient and accurate vertical dynamic model for the ride comfort analysis is developed and implemented in a commercial object-oriented modeling (OOM) software Dymola (2015 FD01) which uses the open-source code Modelica. This model includes car body flexibility with the assembling of a rigid body approach. The developed model is compared to a three-dimensional vehicle model in the commercial Vampire software (Pro V5.50) at different velocities. For the vertical ride comfort analysis, the ISO 2631-1 standard was used for both the developed model and the three-dimensional model. The results are presented as acceleration history and $a^{wrms}$—weighted r.m.s (root mean square) of accelerations—as required by the standard. The developed model has shown its feasibility in terms of its efficiency and accuracy for the vertical ride comfort analysis. The accuracy of the model is evidenced by the fact that the car body vibration level at high speeds shows minor differences compared to the results of the Vampire, which is a validated commercial software in the area of rail vehicle dynamics. The approach involving the assembly of rigid bodies is applied for the first time for high-speed trains in dynamical modelling, with flexible car bodies for ride comfort analysis. Furthermore, it can be used for parametrical studies focusing on ride comfort, thereby offering a quite beneficial framework for addressing the challenges of ride comfort analysis in high-speed rail vehicles. Improvements for and analyses of other aspects are also possible, since the optimization and other useful libraries are readily available in Dymola/Modelica. Full article

Track smoothness has become an important factor in the safe operation of high-speed trains. In order to ensure the safety of high-speed operations, studies on track smoothness detection methods are constantly improving. This paper presents a track irregularity identification method based on CNN-Bi-LSTM and predicts track irregularity through car body acceleration detection, which is easy to collect and can be obtained by passenger trains, so the model proposed in this paper provides an idea for the development of track irregularity identification method based on conventional vehicles. The first step is construction of the data set required for model training. The model input is the car body acceleration detection sequence, and the output is the irregularity sequence of the same length. The fluctuation trend of the irregularity data is extracted by the HP filtering (Hodrick Prescott Filter) algorithm as the prediction target. The second is a prediction model based on the CNN-Bi-LSTM network, extracting features from the car body acceleration data and realizing the point-by-point prediction of irregularities. Meanwhile, this paper proposes an exponential weighted mean square error with priority inner fitting (EIF-MSE) as the loss function, improving the accuracy of big value data prediction, and reducing the risk of false alarms. In conclusion, the model is verified based on the simulation data and the real data measured by the high-speed railway comprehensive inspection train. Full article

With the advent of modern, high-speed electrified rail systems, there has been increasing concern about electromagnetic safety in rail carriages. The aim of this study was to assess the electromagnetic safety of passengers on trains by utilizing advanced 3D electromagnetic simulation software. A comprehensive model of the electromagnetic environment experienced by passengers on a CR400AF train, specifically under the influence of catenary radiation, was constructed. We analyzed the magnetic field strength, electric field strength, and current density in the brains of 20 passengers in various positions in the train. The findings revealed that among the 20 passengers analyzed, the maximum and minimum magnetic induction intensity recorded in the brain were 8.41 and 0.01 $\mathsf{\mu }\mathrm{T}$, respectively. The maximum and minimum induced electric field intensities were 1110 and 10 $\mathsf{\mu }\mathrm{V}/\mathrm{m}$, respectively. Lastly, the maximum and minimum induced current densities were 1200 and 10 ${\mathsf{\mu }\mathrm{A}/\mathrm{m}}^2$, respectively. The results show that when people ride on the CR400AF train, the magnetic induction intensity, induced electric field strength, and induced current density in the brain are below the recommended basic limits of exposure to power frequency electromagnetic fields in the guidelines of the International Committee on Non-Ionizing Radiation Protection. The power frequency magnetic field generated by the catenary can be effectively shielded by the aluminum alloy car body. The final result of this study indicates that the electromagnetic exposure from the contact wire at the level 25 kV does not pose a threat to the health of passengers on the CR400AF train. Full article

In recent years, the research and development of high-speed trains has advanced rapidly. The main development trends of high-speed trains are higher speeds, lower energy consumption, higher safety, and better environmental protection. The realization of a lightweight high-speed car body is one of the key features in the development trend of high-speed trains. Firstly, the basic dimensions of the car body’s geometric model are determined according to the external dimensions of the body of a CRH EMU, and the specific topology optimization design domain is selected to establish the finite element analysis model; secondly, the strength and modal analyses of the topology optimization design domain are carried out to check the accuracy of the design domain and provide a comparative analysis for subsequent design. Then, the variables, constraints, and objective functions of the topology optimization design are determined to establish the mathematical model of topology optimization, and the design domain is calculated for topology optimization under single and multiple conditions, respectively. Finally, based on the topology optimization calculation results, truss-type reconstruction modeling is carried out for the car body’s side walls, roof, underframe, end walls, and other parts. Compared with the conventional EMU body structure, the weight of the reconstructed body structure is reduced by about 18%. The results of the finite element analysis of the reconstructed car-body structure prove the reliability and safety of the structure, indicating that the reconstructed car-body scheme meets the corresponding performance indicators. Full article

The body of a high-speed train is a composite structure composed of different materials and structures. This makes the design of a noise-reduction scheme for a car body very complex. Therefore, it is important to clarify the key factors influencing sound insulation in the composite structure of a car body. This study uses machine learning to evaluate the key factors influencing the sound insulation performance of the composite floor of a high-speed train. First, a comprehensive feature database is constructed using sound insulation test results from a large number of samples obtained from laboratory acoustic measurements. Subsequently, a machine learning model for predicting the sound insulation of a composite floor is developed based on the random forest method. The model is used to analyze the sound insulation contributions of different materials and structures to the composite floor. Finally, the key factors influencing the sound insulation performance of composite floors are identified. The results indicate that, when all material characteristics are considered, the sound insulation and surface density of the aluminum profiles and the sound insulation of the interior panels are the three most important factors affecting the sound insulation of the composite floor. Their contributions are 8.5%, 7.3%, and 6.9%, respectively. If only the influence of the core material is considered, the sound insulation contribution of layer 1 exceeds 15% in most frequency bands, particularly at 250 and 500 Hz. The damping slurry contributed to 20% of the total sound insulation above 1000 Hz. The results of this study can provide a reference for the acoustic design of composite structures. Full article

High-temperature Superconducting (HTS) maglev trains are vulnerable to the effects of crosswinds when operating at high speeds in open-air conditions, potentially compromising riding comfort and safety. This study established a vehicle dynamic model based on the nonlinear maglev-track relationship and added aerodynamic loads under crosswinds to the train’s simplified load center to address this issue. Using the maximum vibration acceleration limit and the Sperling index, we evaluated the riding comfort of the HTS maglev train under different conditions. Further, the vibration acceleration power spectral density was analyzed to reveal the impact of increasing the train’s operating speed and crosswind speed. The results indicated that the lateral and vertical Sperling index achieved an “excellent” rating, even at crosswind speeds of up to 20.7 m/s when the train was traveling at speeds of up to 600 km/h. However, it was noted that particular attention should be given to the riding comfort in the head car when the speed reaches 600 km/h. Moreover, the influence of the increase in train speed on the vibration frequency domain distribution of the three car bodies and the train’s riding comfort is greater than that of the increase in the crosswind speed. These findings may provide a valuable reference for the future engineering application of the HTS maglev train. Full article

High-speed trains operating in windy areas may accelerate and decelerate frequently to maintain safe travel, especially when passing curves. During acceleration and deceleration, the role of inter-vehicle suspension (IVS) cannot be ignored. The present study aims to evaluate the effect of IVS on the variable speed curve running of trains under crosswinds. To achieve this purpose, a multibody model of a China Railways High-speed 2 (CRH2) high-speed train considering the IVS is established. By inputting the crosswind loads and traction or braking forces to the model and setting curved tracks with different radii and the unloading factor set as safety criterion, the safe running speeds of the train under different crosswind speeds and different track radii were obtained. The difference in the vehicle dynamics considering the IVS and the fixed connection under traction and braking conditions is analyzed. The radius of the curve track significantly affects the safety characteristics of a train under crosswinds, but its impact diminishes for radii greater than 7000 m. The lateral acceleration, movement angle, unloading factor, and derailment coefficient in both acceleration and deceleration cases of car bodies are affected by the IVS. As a consequence, the IVS will lead to lower safe speeds than fixed connections, but it will also convey more realistic and credible train dynamics. Full article

Strong wind–sand flow exerts great potential safety hazards for high-speed train operations. In this paper, we investigate the aerodynamic characteristics of high-speed trains passing through the bridge–road transition section under a wind-blown sand environment. In particular, we adopt the sliding grid method to simulate the changes in aerodynamic pressure on the train surface when the train passes the bridge transition at different speeds and bridge heights. The variation in the aerodynamic lateral force borne by the vehicle body at various times is then obtained. The results reveal that in the wind–sand environment, when a train drives from the bridge to the embankment, the pressure values on both the windward and leeward sides of the train change abruptly, with the most obvious increase in the lateral force of the head car. Moreover, the abrupt change in pressure increases with the speed of the lateral wind–sand flow. The differential pressure force of the train on the embankment is larger where the differential pressure force on both sides of the head train is the largest. When the train is running in the opposite direction, the differential pressure force on both sides of the train decreases. Compared with the lateral wind condition, the lateral force at different positions of the train under the wind–sand condition exceeds that under the non-sand condition. The average increases in the train body are approximately 17.6% (10 m/s), 10.5% (20 m/s) and 9.5% (30 m/s), which will cause passengers to experience an obvious “shaking” phenomenon. Full article

The evaluation of the vibration behavior of railway vehicle car bodies based on the results of numerical simulations requires the adoption of an appropriate theoretical model of the suspension which considers the important factors that influence the vibration level of the car body. In this paper, the influence of the secondary suspension model on the vertical vibration behavior of the railway vehicle car body is investigated, based on the results of numerical simulations on the frequency response functions of the acceleration, the power spectral density of the acceleration and the root mean square of the acceleration of the car body. Numerical simulation applications are developed based on a rigid-flexible coupled vehicle model with seven degrees of freedom, corresponding to car body vibration modes: bounce, pitch, and first vertical bending mode, and bogie vibration modes: bounce and pitch. Four different models of secondary suspension are integrated into the vehicle model, namely a reference model and four analysis models. Analysis models include systems through which the pitch vibration of the bogies is transmitted to the car body, influencing its vibration behavior and, respectively, a system that takes the relative angular displacement between the car body and the bogie and a system that models the transmission system of the longitudinal forces between the bogie and the car body are analyzed. The effects of these two systems on the vibration behavior of the railway vehicle car body are analyzed both for each system separately and together. In the conclusions of the paper, the influence of the secondary suspension model on the vibration level at the resonance frequencies of the vertical bending of the car body and the pitch of the bogie is pointed out. It also highlights the important contribution of the transmission system of the longitudinal forces between the bogie and the car body in transmitting pitch vibrations of the bogies to the car body, with effects on the vibration level of the car body at high speeds. Full article

Due to factors such as uneven guide rails and airflow disturbance in the hoistway, high-speed elevators may experience significant vibrations during operation. This paper proposes an optimized fractional-order PID (FOPID) method to suppress vibrations of high-speed elevators. First, an accurate horizontal vibration model is established for the elevator car, in which the car frame and body are separate. Then, taking the control cost and the system performance as objective functions, we obtained an optimized FOPID controller based on multi-objective genetic algorithm optimization. Finally, the effectiveness of the controller in reducing elevator vibration was verified through numerical simulation. The results indicate that the horizontal acceleration controlled by the FOPID controller is reduced by about 68% compared to the case without a controller and about 25% compared to the conventional PID controller. Full article

For high-tech manufacturing industries, developing large-scale complex nonlinear dynamic systems must be taken as one of the basic works, formulating problems to be solved, steering system design in a more preferable direction, and making correct strategic decisions. By using effective tools of big data mining, Dynamic Design Methodology was proposed to establish a technical platform for Multidiscipline Design Optimization such as High-Speed Rolling Stock, including three key technologies: analysis graph of full-vehicle stability properties and variation patterns, improved transaction strategy of flexible body to MBS interface, seamless collaboration with weldline fatigue damage assessments through correct Modal Stress Recovery. By applying the above methodology, a self-adaptive improved solution was formulated with optimal parameter configuration, which is one of the more favorable options for higher-speed bogies. While within a velocity (140–200) km/h at λ_e < 0.10, car body instability’s influence on ride comfort can be easily improved by using a semi-active vibration reduction technique between inter-vehicles through outer windshields. Comprehensive evaluations show that only under rational conditions of wheel-rail matching, i.e., 0.10 ≥ λ_eN > λ_emin and λ_emin = (0.03–0.06), can this low-cost solution achieve the three goals of low track conicity, optimal route planning, and investment benefit maximization. So, rail vehicle experts are necessary to collaborate and innovate intensively with passenger transportation and steel rail ones. Specifically, by adopting rail grinding treatment, occurrence probability is controlled at 85% and 5% for track conicity of (0.03–0.10) and (0.25–0.35). By optimizing routing planning, operating across dedicated lines of different speed grades can achieve self-cleaning of central hollow tread wear over time. According to the inherent rigid-flex coupling relationship, geometric nonlinearities of worn wheel-rail contact should be avoided as much as possible for HSR practices. Only under weak coupling interfaces in the floor frame can the structural integrity of an aluminum alloy car body be ensured. Full article

A crucial material comprising a pneumatic tire is rubber. In general, the tire, or more specifically, the hysteresis effects brought on by the deformation of the part made of rubber during the procedure, heat up the part. In addition, the tire temperature depends on several factors, including the inflation pressure, automobile loading, car speed, road tire, the environmental conditions, and the tire geometry. This work focuses on using simulations to calculate the temperature and generated heat flow distributions of a rolling tire with constant velocity using the finite element method. For the sake of simplicity, it is assumed that the only components of the tire are rubber, body-ply, bead wire, and the rim. While the other components are believed to be made of a linear elastic material, the nonlinear mechanical behavior of the rubber is characterized by a Mooney–Rivlin model. Investigations are conducted into the combined effects of vehicle loads and inflation pressure. Hysteresis energy loss is used as a bridge to link the strain energy density to the heat source in rolling tires, and their temperature and heat flow distributions may be determined by steady-state thermal analysis. Thanks to the state-of-the-art computing method, the time required for connected 3D dynamic rolling tire simulations is reduced. The simulation outcomes demonstrate that the maximum temperature in this paper is attained with high weights, high velocities, and low inner inflated pressures. Overall, the maximum temperature is increased with the rise of all three variables. Moreover, the rise of the friction coefficient between the tread and road surface moves the high-temperature area towards the tread/sidewall connection area. Full article