摘要
铁路桥梁健康监测系统收集的振动信号具有明显的分段特征与非平稳特征。为满足桥梁健康监测实际应用中快速分割自由振动信号与受迫振动信号的需求,研究了适用于健康监测系统的信号分割预处理方法。该方法基于VMD与平方马氏距离构造信号特征指数,通过辨别特征指数上包络曲线发展趋势,实现信号受迫振动段与自由振动段的分割。以某铁路桥梁振动信号为例,建立有限元模型,采用Lanczos算法计算结构前2阶频率分别为1.696、3.691Hz,与频域分析结果分别相差0.4%、3.2%,验证了模型的合理性,也表明该分割方法对结构前几阶固有频率的识别效果较好。
The vibration signals collected by railway bridge health monitoring systems have obvious segmental and non-stationary characteristics.In order to meet the practical application’s requirement for quick segmentation of free and forced vibration signals,a signal segmentation preprocessing method is developed for health monitoring systems.This method establishes a signal characteristic index based on VMD and squared Mahalanobis distance,allowing for the division of forced and free vibration sections by analyzing the development trend of the envelope curve on the characteristic index.Using vibration signals from a railway bridge as a case study,a finite element model is created.The natural frequencies of the first two orders of the structure are calculated using the Lanczos algorithm,yielding values of 1.696 Hz and 3.691 Hz,which correspond to deviations of 0.4%and 3.2%respectively,from the results of frequency domain analysis.This confirms the rationality of the model and demonstrates that the segmentation method effectively identifies the natural frequencies of the initial orders of the structure.
作者
蒋欣
杨泽恒
张周煜
徐海波
朱金前
JIANG Xin;YANG Zeheng;ZHANG Zhouyu;XU Haibo;ZHU Jinqian(School of Civil Engineering and Architecture,Wuhan Institute of Technology,Wuhan Hubei 430074,China;School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan Hubei 430063,China;Hubei Jiaotou Jingchu Construction Management Co.,Ltd.,Jingzhou Hubei 434100,China;Hubei Muzhijun Technology Co.,Ltd.,Ezhou Hubei 436001,China)
出处
《中国铁路》
北大核心
2025年第1期55-60,共6页
China Railway
基金
湖北省自然科学基金计划项目(2022CFB256)
鄂州市科技计划项目重点研发专项(EZ01-005-20220025)。
关键词
铁路桥梁
振动
信号分割
平方马氏距离
特征指数
railway bridge
vibration
signal segmentation
squared Mahalanobis distance
characteristic index
