基于HHT的复合扰动环境中结构基本自振周期优化识别

Optimization and identification of basic natural vibration periods ofstructures in complex disturbance environment based on HHT

基于希尔伯特-黄变换(Hilbert-Huang Transform,简称HHT)方法探索了在风、人为振动及传感器误差等复合干扰及低信噪比条件下脉动信号中与结构本质特征关联频率的优化提取和分析方法。以南昌市某小区临街12层住宅楼为分析对象,在干扰信号较多的白天进行结构脉动信号实测,测试表明,在拾振器所在层有非天然振动干扰时,波形的平稳度及频谱特征改变对后续分析产生了显著影响。在未处理干扰信号、基线偏移等的前提下,分别应用FFT、R/F谱比、HHT 3种方法提取结构基本自振周期,并进行分析效果对比,结果表明,HHT方法展现出良好的信号频率提取能力,同时可以通过余项表达信号基线漂移的误差,优化了建筑结构基本自振周期识别方法,拓展了脉动法使用范围,为规模化结构健康监测预警提供了有效参照。

Based on the Hilbert-Huang transform(HHT)method,the optimal extraction and analysis were explored of the frequency associated with the essential features of the structure in the pulsating signal under the combined interference of wind,artificial vibration and sensor error and the condition of low signal-to-noise ratio(SNR).Taking a 12-story residential building facing a street in Nanchang as the analysis object,the structure pulsation signal was measured during the day when there were more interference signals.Test results show that when there is unnatural vibration interference on the floor where the vibration collector is located,the change of waveform smoothness and that of spectrum characteristics have a significant impact on the subsequent analysis.On the premise that the interference signal and baseline deviation were not processed,three methods of FFT,R/F spectrum ratio and HHT were used to extract the basic natural vibration period of the structure,and the analysis results were compared.Research results show that the HHT method exhibits good signal frequency extraction ability.At the same time,the error of signal baseline drift could be expressed through the remaining terms.The basic natural vibration frequency identification method of building structures is optimized,the application range of pulsation method is expanded,and an effective reference for large-scale structural health monitoring and early warning is provided.