摘要
随机子空间辨识算法(SSI)在识别高层结构动力特性过程中产生虚假模态,干扰了动力特性的自动跟踪。本文通过状态空间模型证明非白噪声是产生虚假模态的原因之一,并进一步针对非白噪声激励提出了基于多元变分模态分解(MVMD)的信号重构方法,剔除由于非白噪声引起的虚假模态;通过Single-Pass聚类算法剔除离散虚假极点,消除其他虚假模态。将上述算法应用于超高层结构的现场实测数据,实现了动力特性的长期自动识别与跟踪。
Stochastic subspace identification(SSI)generates spurious modes in the process of identifying the dynamic characteris⁃tics of high⁃rise structures,which interferes with the automatic tracking of dynamic characteristics.This article has proved that the non⁃white noise excitation is one of the causes of spurious modes,and further proposed a signal reconstruction method based on multivariate variational mode decomposition(MVMD)for non⁃white noise excitation,which removes the influence of non⁃white noise excitation in signals and eliminates spurious modes.A Single⁃Pass clustering algorithm is proposed to eliminate discrete spuri⁃ous poles.The above algorithm has been applied to on⁃site monitoring data of super high⁃rise structures,achieving long⁃term auto⁃matic identification and tracking of dynamic characteristics.
作者
胡卫华
张震
唐德徽
卢伟
滕军
HU Wei‑hua;ZHANG Zhen;TANG De‑hui;LU Wei;TENG Jun(College of Civil and Environmental Engineering,Harbin Institute of Technology(Shenzhen),Shenzhen 518056,China;Guangdong Provincial Key Laboratory of Intelligent and Resilient Structures for Civil Engineering,Shenzhen 518056,China)
出处
《振动工程学报》
EI
CSCD
北大核心
2024年第9期1451-1459,共9页
Journal of Vibration Engineering
基金
国家重点研发计划资助项目(2022YFC3801202)
国家自然科学基金资助项目(52378296,52122804)
深圳市科技研发资金稳定支持计划面上项目(GXWD20220811163144001)
深圳市基础研究项目(JCYJ20220531095013030)。
关键词
高层结构
随机子空间法
多元变分模态分解
动力特性
自动跟踪
high⁃rise structures
stochastic subspace identification
multivariate variational modal decomposition
dynamic performance
automatic tracking
