SSA-based stochastic subspace identification of structures from output-only vibration measurements

Chin Hsiung Loh, Yi Cheng Liu, Yiqing Ni

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.
Original languageEnglish
Pages (from-to)331-351
Number of pages21
JournalSmart Structures and Systems
Volume10
Issue number4
DOIs
Publication statusPublished - 1 Jan 2012

Keywords

  • Covariance-driven SSI
  • Data-driven SSI
  • Operational modal analysis
  • Singular spectrum analysis
  • State-space model
  • Stochastic subspace identification

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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