As a core infrastructure of high-speed railways, ballast layers constituted by graded crushed stones feature noteworthy particle movement compared with normal railways, which may cause excessive settlement and have detrimental effects on train operation. However, the movement behavior remains ambiguous due to a lack of effective measurement approaches and analytical methods. In this study, an image-aided technique was developed in a full-scale model test using digital cameras and a color-based identification approach. A total of 1274 surface ballast particles were manually dyed by discernible colors to serve as tracers in the test. The movements of the surface ballast particles were tracked using the varied pixels displaying tracers in the photos that were intermittently taken during the test in the perpendicular direction. The movement behavior of ballast particles under different combinations of train speeds and axle loads was quantitatively evaluated. The obtained results indicated that the surface ballast particle movements were slight, mainly concentrated near sleepers under low-speed train loads and greatly amplified and extended to the whole surface when the train speed reached 360 km·h. Additionally, the development of ballast particle displacement statistically resembled its rotation. Track vibration contributed to the movements of ballast particles, which specifically were driven by vertical acceleration near the track center and horizontal acceleration at the track edge. Furthermore, the development trends of ballast particle movements and track settlement under long-term train loading were similar, and both stabilized at nearly the same time. The track performance, including the vibration characteristics, accumulated settlement, and sleeper support stiffness, was determined to be closely related to the direction and distribution of ballast particle flow, which partly deteriorated under high-speed train loads.

中文翻译：

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高速铁路道碴颗粒运动的图像辅助分析

作为高速铁路的核心基础设施，由级配碎石构成的道碴层与普通铁路相比，颗粒运动显着，可能导致过度沉降，对列车运行产生不利影响。然而，由于缺乏有效的测量方法和分析方法，运动行为仍然不明确。在这项研究中，使用数码相机和基于颜色的识别方法在全尺寸模型测试中开发了图像辅助技术。总共 1274 个表面道碴颗粒被手动染色为可辨别的颜色，作为测试中的示踪剂。使用在测试过程中沿垂直方向间歇拍摄的照片中显示示踪剂的不同像素来跟踪表面道碴颗粒的运动。定量评估了不同列车速度和轴荷组合下道碴颗粒的运动行为。结果表明，低速列车荷载时，地表道碴颗粒运动较轻微，主要集中在枕木附近，当列车速度达到360 km·h时，地表道碴颗粒运动大幅放大并扩展到整个地表。此外，从统计上看，压载颗粒位移的发展与其旋转相似。轨道振动导致道碴颗粒的运动，具体是由轨道中心附近的垂直加速度和轨道边缘的水平加速度驱动的。此外，列车长期荷载作用下道碴颗粒运动与轨道沉降的发展趋势相似，几乎同时趋于稳定。轨道性能，包括振动特性、累积沉降和枕木支撑刚度，被确定与道碴颗粒流的方向和分布密切相关，在高速列车载荷下，道碴颗粒流的方向和分布会部分恶化。