基于车内振动噪声响应的钢轨波磨状态评估方法

doi:10.3901/JME.2025.22.222

摘要/Abstract

摘要： 为建立车内振动噪声响应与线路钢轨表面波磨状态的映射机制，通过动态时间规整算法(Dynamic time warping, DTW)实现振动、噪声信号与钢轨表面波磨信号的同步，利用自适应小波时频分析方法揭示钢轨波磨对车内振动及噪声时频域的影响，基于机器学习K-means聚类算法和自定义加窗Pearson系数构建车内振动噪声与线路钢轨波磨的映射关系，并以此提出基于车内振动或噪声响应评估钢轨波磨状态的新方法。结果表明，车内噪声和地板垂向振动主频主要由钢轨波磨导致，车内噪声主频分布在400～1 200 Hz范围，车内地板垂向振动主频分布在300～1 000 Hz范围。车内噪声与曲线内外轨波磨的Pearson系数分别在0.82和0.62附近，车内地板垂向振动与曲线内外轨波磨的Pearson系数分别在0.81和0.72附近。基于提出的噪声指数和振动指数评价线路钢轨波磨状态，与现场实测数据保持一致。噪声指数和振动指数可表征线路钢轨波磨的波长和波深幅值，为地铁钢轨波磨的识别提供一种新的方法。

关键词: 地铁, 车内噪声, 车内振动, 钢轨波磨, 关联性分析

Abstract: To establish a mechanism for mapping the relationship between interior train vibration and noise response and the state of the line rail surface corrugation, the dynamic time warping algorithm（DTW） is applied to synchronize vibration or noise signals with rail surface corrugation signals. The adaptive wavelet time-frequency analysis（AWTA） method is used to reveal the influence of rail corrugation on interior train vibration and noise in both the time and frequency domains. A mapping relationship between train interior vibration and noise and line rail corrugation state is constructed by the K-means clustering algorithm and custom windowed Pearson coefficients. A new method is proposed to evaluate rail corrugation state based on interior train vibration or noise response. The results show that the main frequencies of train interior noise and vertical floor vibration are primarily caused by rail corrugation. Specifically, the main frequencies of train interior noise are distributed in the range of 400-1 200 Hz, and the main frequencies of vertical floor vibration are distributed in the range of 300-1 000 Hz. The Pearson coefficients of train interior noise and inner and outer rail corrugation of the curve are around 0.82 and 0.62, respectively. Additionally, the Pearson coefficients of train interior floor vertical vibration and inner and outer rail corrugation of the curve are around 0.81 and 0.72, respectively. The rail corrugation state can be evaluated by the Noise Index and Vibration Index. The results are consistent with the measured data in the field. These indices can characterize the wavelength and amplitude of rail corrugation and provide a new method for identifying subway rail corrugation.

Key words: metro, rail corrugation, train interior noise, train interior vibration, correlation analysis

中图分类号:

U216

王阳, 肖宏, 张智海, 叶利宾, 金锋, 方树薇. 基于车内振动噪声响应的钢轨波磨状态评估方法[J]. 机械工程学报, 2025, 61(22): 222-236.

WANG Yang, XIAO Hong, ZHANG Zhihai, YE Libin, JIN Feng, FANG Shuwei. Rail Corrugation State Assessment Method Based on Train Interior Vibration and Noise Response[J]. Journal of Mechanical Engineering, 2025, 61(22): 222-236.

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