arrow
Return

Frequency Domain State Space-Based Mode Decomposition Framework

delete2019-07-01
delete9
PRE
AI
J
Jae‐Seung Hwang *
D
Dae Kun Kwon
A
Ahsan Kareem
DOI:10.1061/(ASCE)EM.1943-7889.0001624delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
For system identification of structures using responses comprised of contributions from multiple modes, one usually decomposes responses into individual modes prior to identifying parameters such as natural frequency, damping, and mode shapes. Conventional mode decomposition techniques such as the frequency domain decomposition (FDD) and the blind source separation (BSS) have been successfully applied to estimate modal matrix (mode shapes) from output-only data. Most of these techniques are formulated in physical coordinates, so the classical damping assumption is implicitly invoked. However, structures with auxiliary damping devices, which have been increasingly incorporated into modern structures over the last several decades, represent a nonclassically damped system. This arrangement may result in modal responses that are not completely decomposed by conventional techniques. In addition, these techniques may suffer from failing to decompose closely spaced modes. To overcome these limitations, a new state space-based mode decomposition (SSBMD) framework is proposed here that involves an optimization procedure to estimate the modal matrix from the eigen problem. Furthermore, the framework can be expanded to identify mode shapes not only in the state-space coordinates but also in physical coordinates, depending on the established performance index. To validate the proposed framework, this study examined a heavily damped three-degree-of-freedom (DOF) nonclassically damped system by way of numerical simulation and the wind-induced full-scale acceleration response of a 40-story steel-framed building with closely spaced modes.
Keywords:
Mode decomposition
State space
Physical coordinate
Nonclassically damped system
Closely spaced modes
Performance index
Frequency domain decomposition
Blind source separation
Independent component analysis
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Engineering Fracture Mechanics cover
Engineering Fracture Mechanics
IF:
5.3
Papers:
5.0K
Citations:
3.2W

Organization

U
University of Notre Dame
Scholars:
1.2W
Papers: 1.1W
Citations: 1.7W
C
Chonnam National University
Scholars:
1.7W
Papers: 1.6W
Citations: 1.4W
Cited Papers

Cited Papers

Sociodemographic factors and failure of hip arthroplasty
err1999-12-01
err0
errOAAI
errK. Inoue; T. Ushiyama; Y. Tani; S. Hukuda
errShare
errSave
Modified Cross-Correlation Method for the Blind Identification of Structures
err2010-07-01
err71
PREAI
errHazra, B.; Roffel, A. J.; Narasimhan, S.; Pandey, M. D.
errShare
errSave
Blind identification of soil-structure systems
err2013-02-01
err32
PREAI
errGhahari, S. F.; Ghannad, M. A.; Taciroglu, E.
errShare
errSave
researcher View more