Evaluating the performance of distributed approaches for modal identification

Sriram S. Krishnan; Zhuoxiong Sun; Ayhan Irfanoglu; Shirley J. Dyke; Guirong Yan

doi:10.1117/12.882143

Evaluating the performance of distributed approaches for modal identification

Sriram S. Krishnan
, Zhuoxiong Sun
, Ayhan Irfanoglu
, Shirley J. Dyke
, Guirong Yan

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

6 Citations (Scopus)

Abstract

In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

Original language	English
Title of host publication	Proceedings of the 2011 SPIE Conference on Smart Structures and Materials, 6-10 March 2011, Town and Country Resort and Convention Center, San Diego, California, USA
Publisher	SPIE
Number of pages	10
DOIs	https://doi.org/10.1117/12.882143
Publication status	Published - 2011
Event	SPIE Conference on Smart Structures and Materials - Duration: 6 Mar 2011 → …

Conference

Conference	SPIE Conference on Smart Structures and Materials
Period	6/03/11 → …

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10.1117/12.882143

Cite this

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title = "Evaluating the performance of distributed approaches for modal identification",

abstract = "In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.",

author = "Krishnan, \{Sriram S.\} and Zhuoxiong Sun and Ayhan Irfanoglu and Dyke, \{Shirley J.\} and Guirong Yan",

year = "2011",

doi = "10.1117/12.882143",

language = "English",

booktitle = "Proceedings of the 2011 SPIE Conference on Smart Structures and Materials, 6-10 March 2011, Town and Country Resort and Convention Center, San Diego, California, USA",

publisher = "SPIE",

note = "SPIE Conference on Smart Structures and Materials ; Conference date: 06-03-2011",

}

Krishnan, SS, Sun, Z, Irfanoglu, A, Dyke, SJ & Yan, G 2011, Evaluating the performance of distributed approaches for modal identification. in Proceedings of the 2011 SPIE Conference on Smart Structures and Materials, 6-10 March 2011, Town and Country Resort and Convention Center, San Diego, California, USA. SPIE, SPIE Conference on Smart Structures and Materials, 6/03/11. https://doi.org/10.1117/12.882143

Evaluating the performance of distributed approaches for modal identification. / Krishnan, Sriram S.; Sun, Zhuoxiong; Irfanoglu, Ayhan et al.
Proceedings of the 2011 SPIE Conference on Smart Structures and Materials, 6-10 March 2011, Town and Country Resort and Convention Center, San Diego, California, USA. SPIE, 2011.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Evaluating the performance of distributed approaches for modal identification

AU - Krishnan, Sriram S.

AU - Sun, Zhuoxiong

AU - Irfanoglu, Ayhan

AU - Dyke, Shirley J.

AU - Yan, Guirong

PY - 2011

Y1 - 2011

N2 - In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

AB - In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

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UR - http://spie.org/x47603.xml

U2 - 10.1117/12.882143

DO - 10.1117/12.882143

M3 - Conference Paper

BT - Proceedings of the 2011 SPIE Conference on Smart Structures and Materials, 6-10 March 2011, Town and Country Resort and Convention Center, San Diego, California, USA

PB - SPIE

T2 - SPIE Conference on Smart Structures and Materials

Y2 - 6 March 2011

ER -

Evaluating the performance of distributed approaches for modal identification

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