Damage detection using frequency domain ARX models and extreme value statistics

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Description

Structural health monitoring (SHM) is fast becoming a field of great importance as engineers seek for new ways to ensure the safety of structures throughout their designed lifetime. Current methods for analyzing the dynamic response of structures often use standard frequency response functions to model linear system input/output relationships. However, these functions do not account for the nonlinear response of a system, which damage often introduces. In this study, an auto-regressive model with exogenous inputs (ARX) in the frequency domain is used to extract damage sensitive features, explicitly considering the nonlinear effect in the frequency domain. Furthermore, because of the ... continued below

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8 p.

Creation Information

Fasel, T. R. (Timothy R.); Sohn, H. (Hoon) & Farrar, C. R. (Charles R.) January 1, 2002.

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Description

Structural health monitoring (SHM) is fast becoming a field of great importance as engineers seek for new ways to ensure the safety of structures throughout their designed lifetime. Current methods for analyzing the dynamic response of structures often use standard frequency response functions to model linear system input/output relationships. However, these functions do not account for the nonlinear response of a system, which damage often introduces. In this study, an auto-regressive model with exogenous inputs (ARX) in the frequency domain is used to extract damage sensitive features, explicitly considering the nonlinear effect in the frequency domain. Furthermore, because of the non-Gaussian nature of the extracted features, extreme value statistics (EVS) is employed to develop a robust damage classifier. The applicability of the ARX model combined with EVS to nonlinear damage detection is demonstrated using vibration data obtained from a laboratory experiment of a three-story building model.

Physical Description

8 p.

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  • Submitted to: IMAC XXI: Conference on Structural Dynamics, Kissimmee, FL, February 3-6, 2003

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  • Report No.: LA-UR-02-6587
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 976401
  • Archival Resource Key: ark:/67531/metadc929240

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • January 1, 2002

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 12, 2016, 6:27 p.m.

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Fasel, T. R. (Timothy R.); Sohn, H. (Hoon) & Farrar, C. R. (Charles R.). Damage detection using frequency domain ARX models and extreme value statistics, article, January 1, 2002; United States. (digital.library.unt.edu/ark:/67531/metadc929240/: accessed November 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.