High-speed Railway最新文献

High speed railway technologies are rapidly development in the world. The total distance of the high speed railway is more than 40,000 kilometers in China, and many types of high speed Electrical Multi-Units (EMUs) are operated. The top operation velocity of the train reaches 350 km/h. New science and technologies are developing rapidly. New generation technologies such as the information technology, intelligent manufacturing, new material and processing, innovating design philosophy have revolutionary influence on the high speed train. It promotes the high speed train performance such as intelligence, reliable operation and environment-friendly. Based on many years investigation of the trend of the technology development and requirement of general public, the trend of technology development in five aspects are presented in this paper. The five aspects include economic applicability, high speed and high efficiency, green and low carbon, intelligent safety, comfortable and high quality.

Image detection based on machine learning and deep learning currently has a good application prospect for railway fault diagnosis, with good performance in feature extraction and the accuracy of image localization and good classification results. To improve the speed of locating small target objects of fasteners, the YOLOv5 framework model with faster algorithm speed is selected. To improve the classification accuracy of fasteners, YOLOv5-based heavy-duty railway rail fastener detection is proposed. The anchor size is modified on the original basis to improve the attention to small targets of fasteners. The CBAM (Convolutional Block Attention Module) module and TPH (Transformer Prediction Head) module are introduced to improve the speed and accuracy issues. The rail fasteners are divided into 6 categories. Experiment comparisons show that before the improvement, the MAP@ 0.5 value of all categories are close to the peak of 0.989 after the epoch of 150, and the F1 score approaches 1 with confidence in the interval (0.2, 0.95). The improved mAP@ 0.5 value approached the highest value of 0.991 after the epoch of 75, and the F1 score approached 1 with confidence in the interval (0.01, 0.95). The experiment results indicate that the improved YOLOv5 model proposed in this paper is more suitable for the task of detecting rail fasteners.

With the rapid development of railway transportation, higher requirements for capacity are increasing and amount of communication, computer and control technologies are applied in train control systems which is the popular method for train control. The application of 3 C brings the enhancement of railway transportation performance. However, the number of internal and external cyber security threats is rising, which could lead to some railway accidents. On the other hand, safety is the core of the design process for railway but security is rarely considered due to the closure of traditional railway systems. As cyber security is threatening the normal operation of industrial control systems and the critical infrastructure, security issues of train control systems should be paid more attention as railway transportation play an important role for society and economy. However, due to the safety-critical characteristics, safety assessment and analysis works have been performed for a long time, but cyber security related works are rarely considered. In the paper, we demonstrate the security situation of train control systems based on the inherent features and the experience of other industrial control systems, where the technical defects and potential threats are summarized. According to the practical engineering experience, the current security protection strategies are illustrated, which shows the popular security protection methods are limited and cannot realize the defense-in-depth. Finally, some research challenges of security issues of train control systems are identified.

Today, it is difficult to further improve the dynamic performance of rail vehicles with conventional passive suspension. Also, simplified vehicle respectively running gear layouts that significantly could reduce vehicle weights are difficult to realize with modern requirements on passenger vibration comfort and wheel and rail wear. Active suspension is a powerful technology that can improve the vehicle dynamic performance and make simplified vehicle concepts possible. The KTH Railway group has, together with external partners, investigated active suspensions both numerically and experimentally for 15 years. The paper provides a summary of the activities and the most important findings. One major project carried out in close collaboration with the vehicle manufacturer Bombardier and the Swedish Transport Administration was the Green Train project, where a 2-car EMU test bench was used to demonstrate different active technologies. In ongoing projects, a concept of single axle - single suspension running gear is developed with active suspension both for comfort improvement and reduced wheel wear in curves. The results from on-track tests in the Green Train project were so good that the technology is now implemented in commercial trains and the simulation results for the single-axle running gear are very promising.

This paper reports a method for strand tension in anchor spans considering rotation. A kind of co-moved coordinate system, a saddle local coordinate system, was set up. This system implemented the rotation of the splay saddle through the rotation of the coordinate system, and all calculations proceeded in this coordinate system. Considering the rotation of the anchoring surface by the rotation of the local coordinate system of the anchoring surface, the anchorage point coordinates of strands were transformed to the local saddle coordinate system. There was a two-layer iteration adopted in the calculation. In the inner iteration, the cable force at the end of the vertical bend was taken as the variable, and the ordinate of the anchorage point was taken as the target value. In the outer iteration, the vertical tangential angle at the end of the vertical bend was taken as the variable, and the ordinate of the anchorage point was taken as the target value. The method carried out the rotation of the splay saddle and anchor surface and was simple, convenient and without approximation. The effect of rotation was considered precisely; it showed stability during the process of two-layer iteration, powerful adaptation and higher efficiency and had been successfully applied in the construction control of the Wufengshan Yangtze River Bridge, the world's first kilometer-level combined highway and railway suspension bridge.

In order to make further study on the mechanical property of CRTSIII type slab non-ballast track structures, which was self-designed in China, based on the method of the multiscale finite element model (FEM), the traditional FEM of slab non-ballast track structures was improved. The multiscale FEM of CRTSIII type slab non-ballast track structures was established based on the general finite element program ABAQUS. Then the comparative calculation was made between various FEMs, showing that the high solution precision, fast modelling speed and high solution efficiency could be obtained. Therefore, the multiscale FEM was suitable for the parametric study on mechanical behaviour of CRTSIII type slab non-ballast track structures, and then the key influence factor and constructions could be optimized.

In the service period, the instability of ballastless track bed are mostly related to the damage of interlayers which are mainly resulted from the incompatible thermal deformation of interlayers. The temperature field within the ballastless track bed shows significant non-uniformity due to the large difference in the materials of various structure layers, leading to a considerable difference in the force bearing of different structure layers. Unit Ballastless Track Bed (UBTB) is most significantly affected by temperature gradient. The thermal deformation of interlayers within UBTB follows the trend of ellipsoid-shape buckling under the effect of the temperature gradient, resulting in a variation of the contact relationship between structure layers and a significant periodic irregularity on the rail. When the train travels on the periodically irregular rail, the structure layers are locally contacted, and the contact zone moves with the variation of the wheel position. This wheel-followed local contact greatly magnifies the interlayer stress, causes interlayer damage, and leads to a considerable increase in the bending moment of the track slab. Continuous Ballastless Track Bed (CBTB) is most significantly affected by the overall temperature variation, which may cause damage to the joint in CBTB. Under the combined action of the overall temperature rise and the temperature gradient, the interlayer damage continuously expands, resulting in bonding failure between structural layers. The thermal force in the continuous track slabs will cause the up-heave buckling and the sudden large deformation of the track slab, and the loss of constraint boundary of the horizontal stability. For the design of a ballastless track structure, the change of bearing status and structural damage related to the incompatible thermal deformation of interlayers should be considered.

The current High-Speed Railway (HSR) communications increasingly fail to satisfy the massive access services of numerous user equipment brought by the increasing number of people traveling by HSRs. To this end, this paper investigates millimeter-Wave (mmWave) extra-large scale (XL)-MIMO-based massive Internet-of-Things (IoT) access in near-field HSR communications, and proposes a block simultaneous orthogonal matching pursuit (B-SOMP)-based Active User Detection (AUD) and Channel Estimation (CE) scheme by exploiting the spatial block sparsity of the XL-MIMO-based massive access channels. Specifically, we first model the uplink mmWave XL-MIMO channels, which exhibit the near-field propagation characteristics of electromagnetic signals and the spatial non-stationarity of mmWave XL-MIMO arrays. By exploiting the spatial block sparsity and common frequency-domain sparsity pattern of massive access channels, the joint $\text{AUD}$ and CE problem can be then formulated as a Multiple Measurement Vectors Compressive Sensing (MMV-CS) problem. Based on the designed sensing matrix, a B-SOMP algorithm is proposed to achieve joint AUD and CE. Finally, simulation results show that the proposed solution can obtain a better AUD and CE performance than the conventional CS-based scheme for massive IoT access in near-field HSR communications.