Debonding Analysis and Identification of the Interface Between Sleeper and Track Slab for Twin-Block Slab Tracks

厚板 磁道(磁盘驱动器) 有限元法 振动 加速度 块(置换群论) 结构工程 地质学 材料科学 计算机科学 接口(物质) 声学 几何学 复合材料 工程类 物理 数学 操作系统 经典力学 毛细管作用 毛细管数
作者
Wei Du,Shijie Deng,Juanjuan Ren,Zeming Zhao,Zhen Wei,Kaiyao Zhang,Wenlong Ye
出处
期刊:International Journal of Structural Stability and Dynamics [World Scientific]
卷期号:21 (14) 被引量:12
标识
DOI:10.1142/s0219455421400113
摘要

For China Railway Track System (CRTS) I twin-block slab tracks, the interface between the sleeper and track slab is susceptible to damage under the coupled effect of long-term train load and external environment factors. In order to analyze the damage behavior and identify the type of debonding at the interface, this paper established a three-dimensional finite element model and introduced the cohesion zone model and concrete damaged plasticity model to simulate the interface damage and the inner-layer damage of the track slab, respectively. The interface debonding induced by the temperature effect was analyzed, and the debonding types were identified based on the obtained vertical vibration responses of the sleeper surface under the train load. The results reveal that the damage mainly occurs on the bottom and lateral sides at the interface under the temperature load. The track model can be refined further to obtain higher analysis accuracy with acceptable calculation time using the sequential loading method. The 26 damage features derived from the time domain, frequency domain, and time–frequency domain are in good representativeness in reflecting the damage information hidden in the vibration signals. Among them, the peak values (maximum vertical acceleration of the sleeper) are 55.0, 56.7, 60.3, and 61.6[Formula: see text]m/s 2 for no debonding, debonding on the lateral side, debonding at the bottom, and debonding on the longitudinal side of the interface under train load, respectively. Moreover, the identification accuracy of the debonding type can reach 93.75% combining the particle swarm algorithm and support vector machine. It indicates that the proposed identification method is effective and reliable to provide theoretical guidance for developing scientific maintenance and repair strategies for twin-block slab tracks.
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