摘要
振动信号是结构健康监测中一种主要的数据类型。从振动信号中可以识别出模态频率、阻尼等结构动力特性指标。但是从结构健康监测系统采集到的振动信号往往含有噪声和异常,这对结构动力特性指标的识别带来严重的影响。为了提高动力特性指标的识别精度,文章根据结构振动信号的特点,提出一种结构健康监测场景的振动信号预处理方法。首先采用箱型图标注离群值,使用三次样条插值法插补缺失值;利用基于中心频率法的变分模态分解(VMD)对原始信号进行分解,通过峭度值筛选有效的本征模态函数分量(IMF),再将有效分量重构。通过模拟信号及工程实测信号两个案例考察该方法的预处理效果。结果显示,经过所提出方法处理的信号,其信噪比效果最佳,模态频率均能被精准识别。因此,文章提出的方法能对振动信号进行有效清洗,有利于提高动力特性指标识别精度。
Vibration signal is a primary type of data in structural health monitoring.Modal frequencies,damping,and other dynamic characteristics of structures can be identified from vibration signals.However,vibration signals collected from structural health monitoring systems often contain noise and anomalies,which seriously affect the identification of structural dynamic characteristic indicators.In order to improve the accuracy of dynamic characteristic indicator identification,this paper proposes a structural vibration signal preprocessing method based on the characteristics of structural vibration signals.Firstly,outlier values are annotated by using boxplot,and missing values are interpolated using cubic spline interpolation.The original signal is decomposed using variational mode decomposition(VMD)based on the center frequency method,and effective intrinsic mode function(IMF)components are selected through kurtosis value filtering,followed by reconstruction of the selected components.The preprocessing effect of the proposed method is examined through two cases:simulated signals and engineering measured signals.The results show that signals processed by the proposed method exhibit the best signal-to-noise ratio,and modal frequencies can be accurately identified.Therefore,the proposed method effectively cleans vibration signals,which is beneficial for improving the accuracy of dynamic characteristic indicatoridentification.
作者
叶婉玲
饶瑞
YE Wan-ling;RAO Rui(Research Center for Wind Engineering and Engineering Vibration,Guangzhou University,Guangzhou 510006)
出处
《广州建筑》
2024年第5期11-15,共5页
GUANGZHOU ARCHITECTURE
