Mixed Integer Nonlinear Least-Squares Problem for Damage Detection in Truss Structures
Publication: Journal of Engineering Mechanics
Volume 131, Issue 7
Abstract
We present a mixed integer nonlinear least-squares problem for identifying damage in truss structures from their measured response. In detecting damage based on parameter estimation, the number of unknown parameters is often less than that of measurements, which gives rise to nonunique solutions. To overcome the difficulty, we formulate damage detection as a mixed integer nonlinear least-squares problem, where the subset of unknown parameters is sought that best represents damaged sites. To solve the problem, we present four heuristic algorithms based on the greedy algorithm. One is its direct application. The other three select the near-optimal subsets more efficiently by linearizing the error function, by applying the line search, and by grouping unknown parameters. We assess the performance of these algorithms along with conventional regularization methods through numerical experiments, where many synthetic damage cases are tested. The effect of modeling and measurement errors on the estimate is also studied. We found from the numerical experiments that the linearization-based approach was more efficient than the direct application while the two methods gave reasonably accurate estimates.
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Acknowledgment
This research was supported by Grant-in-Aid No. UNSPECIFIED15760425 from the Japan Society for the Promotion of Science.
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Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 131 • Issue 7 • July 2005
Pages: 659 - 667
Copyright
© 2005 ASCE.
History
Received: Apr 9, 2003
Accepted: Nov 9, 2004
Published online: Jul 1, 2005
Published in print: Jul 2005
Notes
Note. Associate Editor: Arif Masud
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