4.4 Article Proceedings Paper

Structural damage assessment using output-only measurement: Localization and quantification

Journal

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/1045389X13498318

Keywords

Stochastic subspace identification; singular value decomposition; Hilbert amplitude spectrum; system realization; damage detection

Funding

  1. National Science Council of the Republic of China, Taiwan [NSC 99-2221-E-002-088-MY3]
  2. Research Program of Excellency of National Taiwan University [102R891702]

Ask authors/readers for more resources

In this article, a systematic way of structural damage assessment algorithm, including identification of damage location and damage quantification, is proposed using output-only measurement. First, the null-space-based and subspace-based damage detection methods are used to confirm the damage severity of a structure. Then, the stochastic subspace identification technique is adopted to identify the time-varying system natural frequencies from the global response measurement. Finally, the novelty index, defined as the Euclidean norm of the time-frequency Hilbert amplitude spectrum of measurement between the intact and the damaged structures, is applied to locate the damage. To quantify the damage, the complete system realization is obtained from the identified modal properties through stochastic subspace identification method. From which, the inter-story stiffness reduction ratio can be identified using the normalized stiffness matrix. For case of limited measurement, the multi-setup operational modal analysis is applied to construct the complete system matrix. Verification of the proposed damage assessment algorithm using response data from a series of shaking table test of a six-story steel structure with the cut in column member to simulate the damage is demonstrated.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available