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For the bogie frame of the CRH2 EMU trailer, Solidworks software was used to establish a solid model of the frame, and then the model was imported into Workbench for finite element analysis. The load conditions obtained were combined according to UIC 515-4 standard, and the static strength and fatigue strength of the frame were evaluated. The results showed as follows: The bogie frame meets the strength requirements specified in the standard.

This subject aims to study the realization of automated continuous assembly of the sealing ring and sealing cover of the holding axle box in the train bogie of the Chinese railway industry. Since the sealing ring and the drive shaft are very precise, the gap is as small as 0.2 mm or less, the outer diameter is 600 mm, the temperature is 150°C, and the weight is 30 kg, so the difficulty of manual assembly is obvious. Aiming at the problems of low efficiency, high labor intensity, and certain safety risks of traditional manual assembly, this paper designs an automated assembly system for robotic hot-assembled sealing rings and sealing covers. The system consists of an operator operation area, a parts preparation area, a shaft parts placement area, and a robotic arm working area, which realizes the automated assembly of the sealing ring and sealing cover. With the innovative design of the gripper at the end of the robotic arm, the system is able to correct errors in the assembly process, thus realizing a precise set of sealing rings. This system improves assembly efficiency, ensures assembly accuracy, and greatly reduces costs. Meanwhile, thermodynamic simulation results show that the system can meet the requirements of assembly temperature under different working conditions.

The bogie system is known as the “legs” of high-speed train (HST), various failures will inevitably occur under large disturbances, high speeds, and heavy loads. Abnormal detection (AD) is an important means to detect the health status of its key components. Nevertheless, the cross-correlation of failures causes the confusion of health data and fault data under highly-coupled components, which leads to the issue of false detection and missing detection. Hence, this paper proposes a dual convolutional autoencoder (d-CAE) network combined with unsupervised domain-adversarial learning for group anomaly detection of bogies. Firstly, the d-CAE adopts temporal window aggregation to construct initial inputs. Afterwards, the domain-adversarial learning strategy is utilized to make the d-CAE realize multi-level encoding and reconstruction of multi-channel time-series. Finally, a parameterized dynamic AD index is designed to accurately establish the health sample guided abnormal decision boundary. The experimental results indicate that the d-CAE is competitive in the aspects of detection accuracy and robustness compared with the state-of-the-art methods.

The performance of high-speed trains heavily relies on the bogie, a critical component supporting the body and steering. Traditional methods for inspecting bogie components, which rely on manual identification, are not just time-consuming but also expensive. Furthermore, deep learning models often face difficulties in handling dimly lit, intricate backgrounds and detecting numerous small objects. To solve these challenges, we propose Bogie-YOLO, a targeted detection model tailored for bogie photography scenes. Bogie-YOLO utilizes the YOLOv5 framework and introduces the Coordinate and Squeeze-and-Excitation Attention Module (CSAM), improving positional information and channel relationships. Additionally, to expedite convergence, we adopt EIoU as the bounding box loss. Experimental results demonstrate an average Precision of 87.9% and an average mAP0.5 of 83.2% on the dataset of key components of train bogies.

The centralized power EMU is a new type of passenger transportation equipment for ordinary-speed railways in China, which can greatly improve the efficiency of ordinary-speed railway passenger transportation and improve passenger travel conditions. This paper conducts long-term dynamic tracking experiments on this new type of railway passenger car, studying the evolution laws of wheel wear, axle box vibration, bogie frame vibration, and car body vibration during long-term service, and analyzing typical vehicle dynamics phenomena that occur in long-term tracking experiments. Various studies have shown that the vehicle can maintain good lateral stationarity throughout the entire wheel reprofile cycle, and the growth rate of equivalent conicity gradually slows down as the mileage increases; However, when the mileage after wheel reprofiling is large, harmonic vibration may occur in individual sections of the frame, leading to abnormal vibration of the control car body at 10 Hz. The vertical vibration of the axle box will significantly increase at the rail joint, and its 70 Hz vibration is transmitted to the frame through the experiment suspension, stimulating the bending mode of the crossbeam of the frame, resulting in a more obvious 70 Hz vibration in the vertical direction of the frame. The RMS of the axle box, frame, and body sleeper does not show significant changes with the rise in mileage following wheel reprofiling.

Bogie frame and body bolster are of vital importance to the reliable operation of the rolling stocks. There are two kinds of test methods for bogie frame and body bolster. One is separate test, and the other is joint test. To effectively detect the strength performance of bogie frame and body bolster as well as to improve the test efficiency, we adopted the method of joint test, and designed the test plan according to the standard. The strength test of bogie frame and body bolster is carried out where load analysis is studied and applied. The structural performance of bogie frame and body bolster is evaluated by means of Goodman fatigue limit diagram.

To address the practical needs for lightweight bogie cladding structures in high-speed trains, this paper proposes a bogie cladding structure based on the composite application of multiple materials such as aluminum alloys and composite materials. Compared to traditional metal material solutions, this structural scheme features lightweight properties and a rational geometric design. In accordance with the requirements of relevant standards such as TB/T 3451-2016 and TB 3548-2019, the static strength of the cladding structure under typical loading conditions was calculated. The static strength simulation analysis results indicate that under the coupled working conditions of a vertical 1 g acceleration, longitudinal 3 g acceleration, and a 3500 Pa aerodynamic pressure, the maximum stress in the metal material parts of the cladding structure is 173.226 MPa, which does not exceed the yield strength of the aluminum alloy material. Additionally, the Tsai-Wu strength factors for the composite material part are all below 1.0, demonstrating that this structural scheme meets the performance requirements specified by the standards.

Balancing the excavator structure is a widely considered topic that directly relies on the operation, the wear of nodes connecting the upper and the lower structures of the excavator and especially on the stability of the excavator at the operational site. The present paper considers the balance of the excavator structures of the SRs 2000 excavator with idealization to some static positions and simplification of the interactions to static ones. This allows positional regard of the most used positions under operating conditions. This approach derives some dependences clarifying the static balancing of the super structure of the excavator to the undercarriage, taking into account the interactions of both the weight parameters, as of the structural units, as of the main external forces. There are derived dependences for determining the load of ballast weights during repair and modernization of excavator structures

A temperature-dependent dynamic landing model for bogie landing gear has been developed in this study to address the deficiency in quantitative environmental temperature considerations for landing gear performance analysis, which is validated by data from both full-scale drop tests and simulations. Analysis of dynamic landing loads and displacements under varying environmental temperatures (from −45°C to +55°C) demonstrates maximum increases of 17% in main buffer’s air spring force, 1.2% in its axial resultant force, 16% in pitch damper’s air spring force and 11% in its axial resultant force, 3.0% in tire radial forces, while total ground vertical load variation remains ≤2.0%, overload coefficient deviation ≤0.03, and damping efficiency fluctuation ≤3.0%, confirming stable landing performance across temperature extremes. Compared to the filling tolerance method, the proposed quantitative temperature analysis reduces extreme-environment vertical ground loads by 7.33%.