First Results on Regularized Time-Varying Operational Modal Analysis

Péter Zoltán Csurcsia; Joannes Schoukens; Bart Peeters

doi:10.1016/j.ifacol.2018.09.112

First Results on Regularized Time-Varying Operational Modal Analysis

Péter Zoltán Csurcsia, Joannes Schoukens, Bart Peeters

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

2 Citations (Scopus)

Abstract

This paper presents an efficient nonparametric time-varying time domain system identification method for the Operational Modal Analysis (OMA) framework. OMA tackles industrial measurements of vibrating structures in real-life operating conditions without the exact knowledge of the excitation signal. In case of time-varying Operational Modal Analysis it is desired to carefully verify and track the vibration behavior, since during flutter appearance, system destruction can occur. In this work a method is provided to estimate the time-varying output autocorrelation function of vibrating structures and applied to a measurement of wind tunnel testing of an airplane. The proposed method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time-invariant systems. Using the proposed methodology, the estimated time-varying two-dimensional output autocorrelation model provides a good data-fit with respect to tracking of varying resonances.

Original language	English
Title of host publication	18th IFAC Symposium on System Identification SYSID 2018
Pages	162-167
Number of pages	6
Volume	51
Edition	15
DOIs	https://doi.org/10.1016/j.ifacol.2018.09.112
Publication status	Published - 1 Jan 2018
Event	18th IFAC Symposium on System Identification: SYSID 2018 - AlbaNova University Center, Stockholm, Sweden Duration: 9 Jul 2018 → 11 Jul 2018 https://www.kth.se/en/eecs/om-oss/konferenser-och-event/sysid2018

Publication series

Name	IFAC-PapersOnLine
ISSN (Print)	2405-8963

Conference

Conference	18th IFAC Symposium on System Identification
Abbreviated title	SYSID 2018
Country/Territory	Sweden
City	Stockholm
Period	9/07/18 → 11/07/18
Internet address	https://www.kth.se/en/eecs/om-oss/konferenser-och-event/sysid2018

Keywords

Bayesian methods
Filtering
Nonparametric methods
Operational Modal Analysis
Software for system identification
Time-varying system identification
smoothing

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10.1016/j.ifacol.2018.09.112

Cite this

@inproceedings{01b79f3bac2444fda31d2bf477de6f6e,

title = "First Results on Regularized Time-Varying Operational Modal Analysis",

abstract = "This paper presents an efficient nonparametric time-varying time domain system identification method for the Operational Modal Analysis (OMA) framework. OMA tackles industrial measurements of vibrating structures in real-life operating conditions without the exact knowledge of the excitation signal. In case of time-varying Operational Modal Analysis it is desired to carefully verify and track the vibration behavior, since during flutter appearance, system destruction can occur. In this work a method is provided to estimate the time-varying output autocorrelation function of vibrating structures and applied to a measurement of wind tunnel testing of an airplane. The proposed method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time-invariant systems. Using the proposed methodology, the estimated time-varying two-dimensional output autocorrelation model provides a good data-fit with respect to tracking of varying resonances.",

keywords = "Bayesian methods, Filtering, Nonparametric methods, Operational Modal Analysis, Software for system identification, Time-varying system identification, smoothing",

author = "Csurcsia, {P{\'e}ter Zolt{\'a}n} and Joannes Schoukens and Bart Peeters",

year = "2018",

month = jan,

day = "1",

doi = "10.1016/j.ifacol.2018.09.112",

language = "English",

isbn = "2405-8963",

volume = "51",

series = "IFAC-PapersOnLine",

pages = "162--167",

booktitle = "18th IFAC Symposium on System Identification SYSID 2018",

edition = "15",

note = "18th IFAC Symposium on System Identification : SYSID 2018, SYSID 2018 ; Conference date: 09-07-2018 Through 11-07-2018",

url = "https://www.kth.se/en/eecs/om-oss/konferenser-och-event/sysid2018",

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TY - GEN

T1 - First Results on Regularized Time-Varying Operational Modal Analysis

AU - Csurcsia, Péter Zoltán

AU - Schoukens, Joannes

AU - Peeters, Bart

PY - 2018/1/1

Y1 - 2018/1/1

N2 - This paper presents an efficient nonparametric time-varying time domain system identification method for the Operational Modal Analysis (OMA) framework. OMA tackles industrial measurements of vibrating structures in real-life operating conditions without the exact knowledge of the excitation signal. In case of time-varying Operational Modal Analysis it is desired to carefully verify and track the vibration behavior, since during flutter appearance, system destruction can occur. In this work a method is provided to estimate the time-varying output autocorrelation function of vibrating structures and applied to a measurement of wind tunnel testing of an airplane. The proposed method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time-invariant systems. Using the proposed methodology, the estimated time-varying two-dimensional output autocorrelation model provides a good data-fit with respect to tracking of varying resonances.

AB - This paper presents an efficient nonparametric time-varying time domain system identification method for the Operational Modal Analysis (OMA) framework. OMA tackles industrial measurements of vibrating structures in real-life operating conditions without the exact knowledge of the excitation signal. In case of time-varying Operational Modal Analysis it is desired to carefully verify and track the vibration behavior, since during flutter appearance, system destruction can occur. In this work a method is provided to estimate the time-varying output autocorrelation function of vibrating structures and applied to a measurement of wind tunnel testing of an airplane. The proposed method is a novel extension of the regularization methods that have been developed for impulse response estimates of linear time-invariant systems. Using the proposed methodology, the estimated time-varying two-dimensional output autocorrelation model provides a good data-fit with respect to tracking of varying resonances.

KW - Bayesian methods

KW - Filtering

KW - Nonparametric methods

KW - Operational Modal Analysis

KW - Software for system identification

KW - Time-varying system identification

KW - smoothing

UR - http://www.scopus.com/inward/record.url?scp=85054373352&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2018.09.112

DO - 10.1016/j.ifacol.2018.09.112

M3 - Conference paper

SN - 2405-8963

VL - 51

T3 - IFAC-PapersOnLine

SP - 162

EP - 167

BT - 18th IFAC Symposium on System Identification SYSID 2018

T2 - 18th IFAC Symposium on System Identification

Y2 - 9 July 2018 through 11 July 2018

ER -

First Results on Regularized Time-Varying Operational Modal Analysis

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Keywords

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