Application and evaluation of classification algorithms to a finite element model of a three-dimensional truss structure for nondestructive damage detection

Gabriel V. Garcia; Norris Stubbs

doi:10.1117/12.274644

23 May 1997 Application and evaluation of classification algorithms to a finite element model of a three-dimensional truss structure for nondestructive damage detection

Gabriel V. Garcia, Norris Stubbs

Author Affiliations +

Proceedings Volume 3043, Smart Structures and Materials 1997: Smart Systems for Bridges, Structures, and Highways; (1997) https://doi.org/10.1117/12.274644
Event: Smart Structures and Materials '97, 1997, San Diego, CA, United States

Abstract

The objective of this paper is to apply and evaluate the relative performance of classification algorithms for nondestructive damage detection (NDD). The classification algorithm are obtained form various forms of Baye's Rule. An established theory of damage localization, which yields information on the location of the damage directly form changes in mode shapes, is selected. Next, the application of classification is performed to the existing theory of damage localization. Expressions for the classification algorithms using the damage indicator functions from the damage localization theory are generated. Criteria for the evaluation of the proposed classification algorithms are then generated. Using the classification algorithms, damage localization is attempted in a numerical model of a 3D truss structure which contains simulated damage at various locations. Finally, the accuracy and reliability of the classification algorithms is evaluated using the established criteria.

Citation Download Citation

Gabriel V. Garcia and Norris Stubbs "Application and evaluation of classification algorithms to a finite element model of a three-dimensional truss structure for nondestructive damage detection", Proc. SPIE 3043, Smart Structures and Materials 1997: Smart Systems for Bridges, Structures, and Highways, (23 May 1997); https://doi.org/10.1117/12.274644

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