Assessment and Detection of Damage in Structural Systems

Shin, S.; Hjelmstad, K.D.

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https://hdl.handle.net/2142/14217 Copy

Description

Title

Assessment and Detection of Damage in Structural Systems

Author(s)

• Shin, S.
• Hjelmstad, K.D.

Issue Date

1994-10

Keyword(s)

• Parameter estimation
• Monte Carlo simulations
• Damage assessment
• System identification

Abstract

This report presents a new damage detection and assessment algorithm based on a system identification method. The algorithm can be used as a non-destructive diagnostic technique to aid in decisions of repair and rehabilitation of existing structures. The developed algorithm is able to detect and assess damage in a structure when the measured data are sparse and polluted with noise. Damage is defined as the reduction in estimated parameters between two time separated inferences. Damage is localized by updating parameter groups hierarchically and assessed by perturbing measured data. Parameter groups are continuously subdivided until all the existing damaged parts in a structural system are completely localized. The measured data are perturbed to examine the sensitivity of each parameter with respect to the measured data, and to thereby provide a statistical basis for assessing damage. The bias of the mean estimate from the baseline value and this bias divided by the standard deviation of the Monte Carlo perturbation sample are calculated as damage indices. The upper limit values for both damage indices are determined from the simulation study for the undamaged baseline structure and are used to determine damage in the existing structure. Case studies are performed to examine the developed algorithm. Simulated static responses are used to identify damaged planar bowstring truss structures. Real measured modal responses from a laboratory experiment are used to identify the cracked cantilever structure.

Publisher

University of Illinois Engineering Experiment Station. College of Engineering. University of Illinois at Urbana-Champaign.

Series/Report Name or Number

Civil Engineering Studies SRS-593

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/14217

Sponsor(s)/Grant Number(s)

• National Science Foundation Grant CES 86-58019
• Army Research Office Contracts DAAL-03-87-K-006, DAAL-03-86-G-0186, and DAAL-03-86-0188

Owning Collections