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基于超声导波的重载铁路断轨监测研究

Study on monitoring broken rails of heavy haul railway based on ultrasonic guided wave.

作者信息

Xu Xining, Wen Ziyu, Ni Yi, Shao Bohuai, Ma Xinyu, Pan Zecheng

机构信息

State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing, 100044, China.

School of Mechanical, Electronic, and Control Engineering, Beijing Jiaotong University, Beijing, 100044, China.

出版信息

Sci Rep. 2024 Apr 15;14(1):8667. doi: 10.1038/s41598-024-59328-5.

Abstract

Real-time monitoring of broken rails in heavy haul railways is crucial for ensuring the safe operation of railway lines. U78CrV steel is a common material used for heavy haul line rails in China. In this study, the semi-analytical finite element (SAFE) method is employed to calculate the dispersion curves and modal shapes of ultrasonic guided waves in U78CrV heavy steel rails. Guided wave modes that are suitable for detecting rail cracks across the entire cross-section are selected based on the total energy of each mode and the vibration energy in the rail head, web, and foot. The excitation method for the chosen mode is determined by analyzing the energy distribution of the mode shape on the rail surface. The ultrasonic guided wave (UGW) signal in the rail is analyzed using ANSYS three-dimensional finite element simulation. The group velocity of the primary mode in the guided wave signal is obtained through continuous wavelet transform to confirm the existence of the selected mode. It is validated that the selected mode can be excited by examining the similarity between the vibration shapes of a specific rail section and all modal vibration shapes obtained through SAFE. Through simulation and field verification, the guided wave mode selected and excited in this study demonstrates good sensitivity to cracks at the rail head, web, and foot, and it can propagate over distances exceeding 1 km in the rail. By detecting the reflected signal of the selected mode or the degree of attenuation of the transmitted wave, long-distance monitoring of broken rails in heavy-haul railway tracks can be achieved.

摘要

重载铁路断轨实时监测对于确保铁路线路安全运行至关重要。U78CrV钢是中国重载线路钢轨常用材料。本研究采用半解析有限元(SAFE)方法计算U78CrV重型钢轨中超声导波的频散曲线和模态形状。基于各模态的总能量以及轨头、轨腰和轨底的振动能量,选择适用于检测整个横截面钢轨裂纹的导波模态。通过分析模态形状在钢轨表面的能量分布来确定所选模态的激励方法。利用ANSYS三维有限元模拟分析钢轨中的超声导波(UGW)信号。通过连续小波变换获得导波信号中主模态的群速度,以确认所选模态的存在。通过检查特定钢轨截面的振动形状与通过SAFE获得的所有模态振动形状之间的相似性,验证所选模态能够被激励。通过模拟和现场验证,本研究中选择并激励的导波模态对轨头、轨腰和轨底的裂纹表现出良好的敏感性,并且能够在钢轨中传播超过1 km的距离。通过检测所选模态的反射信号或透射波的衰减程度,可以实现重载铁路轨道断轨的远程监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5402/11385469/0ea6dbfd1502/41598_2024_59328_Fig1_HTML.jpg

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