DAMAGE ASSESSMENT POTENTIAL OF A NOVEL SYSTEM IDENTIFICATION TECHNIQUE - EXPERIMENTAL VERIFICATION
Abstract (Summary)
Experimental verification of a novel system identification technique that can detect
defects at the element level is successfully accomplished. The method can be used for inservice
health assessment of real structures without disrupting normal operations. This
study conclusively verifies the method.
Analytical verification of the proposed algorithm has been successfully completed
by the research team at the University of Arizona. Vo and Haldar (2004) experimentally
verified the method by conducting tests on fixed-ended and simply supported defect-free
and defective beams. The purpose of this research was to validate the method by
conducting experiments with more realistic structures.
A three-story one-bay steel frame, built to 1/3 scale to fit the experimental facility,
was considered. The frame was excited by harmonic or impulsive excitation forces. The
transverse acceleration responses were collected using capacitive accelerometers. The
angular displacement responses were measured using an autocollimator.
The dynamic responses of the frames were collected by a data acquisition system
with simultaneous sampling capability. Using only experimentally collected response
information and completely ignoring the excitation information, the stiffness of all the
structural elements were identified. The method identified the defect-free frame very
accurately. Defects, in terms of removing a beam, reducing cross sectional area over a
small segment of a beam, and cutting notches in a beam, were introduced. The method
correctly identified the defect location in all cases. Additional sensors were placed
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around the location of the defect in an effort to identify the defect spot more accurately.
The proposed method also successfully identified defect with improved accuracy.
To increase the implementation potential of the proposed method, the defect-free
and defective frames are then identified using limited response information. A two-stage
Kalman filter-based approach is used. It is denoted as Generalized Iterative Least Square
Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. A sub-structure
approach is used for this purpose. The GILS-EKF-UI method also identified the state of
the structure using only limited response information. As expected, in this case the error
in the identification goes up as less information is used. However, the error is much
smaller than other methods currently available in the literature, even when input
excitation was used for the identification purpose. The method is very robust and can
identify defects caused by different types of loadings. The method can be used as a
nondestructive defect assessment technique for structures.
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Bibliographical Information:
Advisor:
School:The University of Arizona
School Location:USA - Arizona
Source Type:Master's Thesis
Keywords:
ISBN:
Date of Publication: