车轮扁疤会影响列车运行舒适性并加速车辆、轨道基础设施部件故障。本文提出一种基于钢轨振动响应的车轮扁疤动态检测和识别方法。通过建立车辆轨道垂向耦合模型和车轮扁疤模型，计算车轮扁疤作用下的钢轨动态响应。比较了不同轨道不平顺、不同列车运行速度以及不同扁疤深度条件下，对钢轨振动响应进行Hilbert-Huang变换（HHT）和高阶谱分析两种方法的车轮扁疤识别能力。利用HHT中的Hilbert谱可以定性区分正常车轮与有扁疤车轮，但该方法会受到轨道不平顺大小的影响。而利用高阶谱分析方法能够定量判断扁疤深度，且识别能力不受轨道不平顺大小及运行速度影响。研究结果表明，利用钢轨振动响应结合高阶谱分析可以有效检测和识别车轮扁疤。
Abstract
Wheel flats will influence ride comfort and result in rapid deterioration of vehicle and infrastructure components. A dynamic detection and identification method of wheel flat is proposed based on the rail vibration responses. A vehicle-track vertical coupling system and wheel flat are modelled and the rail dynamic responses are calculated with the condition of wheel flat. Two methods, Hilbert-Huang transformation (HHT) and higher-order spectrum, are compared which are used to analyze the rail vibration responses and identify the wheel flat. The influence of different track irregularity, train speed and wheel flat depth on the methods are analyzed. The Hilbert spectrum can qualitatively distinguish the normal wheel and the wheel with flats, but the detection ability is affected by the track irregularity. The high-order spectrum can express the different wheel flat depth quantitatively and it isn’t influenced by the track irregularity and train running speed. The investigation showed the rail vibration responses combined with high-order analysis can detect wheel flats effectively.
关键词
钢轨振动响应 /
车轮扁疤 /
车辆轨道耦合模型 /
Hilbert谱 /
高阶谱
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Key words
rail vibration responses /
wheel flats /
vehicle-track coupling model /
Hilbert spectrum /
high-order spectrum
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