Reference-Based Damage Diagnosis through Identification Technique and Embedded Statistical Model
Date Issued
2006
Date
2006
Author(s)
Wu, Ai-Lun
DOI
en-US
Abstract
Structural damage will cause the change of modal characteristics, such as natural frequencies, mode shapes or modal damping. However these dynamic characteristics can not quantify the damage of the structure. The purpose of this paper is to develop a method for damage diagnosis of a sub-structural system and identify the degree of damage which can be interpreted not only on the damage index but also on the percentage of strength and stiffness degradation. Based on parameter identification of component inelastic hysteretic behavior and the proposed statistical damage model, the damage index and the degree of structural damage can be identified.
To develop the statistical damage model a reference inelastic hysteretic behavior (a generalized bi-linear model) is assumed. Three statistical models of response indices are developed: Normalized hysteretic energy (NHE) ,γ-spectrum and reduction factor, using simulation of seismic response data. These models contain the calibration and modification factors of the post-yielding stiffness, the strength and stiffness degradation, and the pinching effects. These models are obtained from statistical analysis.
For constructed statistical model of γ-spectrum and reduction factor , one can used for prediction. On the other hand, based on the measurement of floor structural responses, particularly the structural component restoring force diagram of floor system, the model parameters of the inelastic hysteretic model is identified first. Using the proposed statistical model of normalized hysteretic energy, the damage index as well as the percentage of stiffness and strength degradation can be quantified
This proposed model is verified both numerically and experimentally using RC frame structures. The results indicate that the current approach can quantify the degree of damage of RC frame structure.
Subjects
系統識別
system identification
Type
thesis
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