A swift technique for damage detection of determinate truss structures (2)

Abstract

This paper introduces a novel and robust probable statistical approach for the applied damage detection of determinate truss structures. This technique involves two steps; the first is called most probable damaged element identification step and the second is called probable damage severity prediction step. In the first step, a new index based on modal residual forces plays a major role to independently identify damage-suspected elements for each considered mode. Then among them, the elements, the most probable to damage, are extracted. In the second step, the probable damage severity for each most probable damaged element is individually predicted using a novel statistical approach. Finally, to justify the validity and robustness of the technique, three commonly used bridge trusses including a 29-bar Pratt truss, a 29-bar Warren truss, and finally, a 37-bar K truss under different damage scenarios are thoroughly studied while their modal parameters are corrupted by noise. The obtained results indicate that the method is innovatively capable of swiftly predicting, for determinate truss structures, not only damaged elements but also their damage severities by carrying out solely few structural analyses.