Abstract
The key to detecting damage to civil engineering structures is to find an effective damage indicator. The damage indicator should promptly reveal the location of the damage and accurately identify the state of the structure. We propose to use the distance measures of low-order AR models as a novel damage indicator. The AR model has been applied to parameterize dynamical responses, typically the acceleration response. The premise of this approach is that the distance between the models, fitting the dynamical responses from damaged and undamaged structures, may be correlated with the information about the damage, including its location and severity. Distance measures have been widely used in speech recognition. However, they have rarely been applied to civil engineering structures. This research attempts to improve on the distance measures that have been studied so far. The effect of varying the data length, number of parameters, and other factors was carefully studied.
Original language | English |
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Pages (from-to) | 991-1005 |
Number of pages | 15 |
Journal | Smart Structures and Systems |
Volume | 6 |
Issue number | 9 |
DOIs | |
Publication status | Published - 2010 Dec |
Keywords
- AR model
- Adaptive component weighting (ACW)
- Cepstral metric
- Damage indicator
- Pre-whitening filter
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering