Damage Assessment of a Bridge under Varying Environmental Conditions

It is known that modal parameters such as natural frequencies and mode shapes are sensitive indicators of structural damage. However, they are not only sensitive to damage, but also to the environmental conditions such as, humidity, wind and most important, temperature. For civil engineering structures, modal changes produced by environmental conditions can be equivalent or greater than the ones produced by damage. This paper proposes a damage detection method able to deal with temperature variations. The objective function correlates mode shapes and natural frequencies, and a Parallel Genetic Algorithm handles the inverse problem. The numerical model of the structure assumes that the elasticity modulus of the materials is temperature dependent. The algorithm updates the temperature and damage parameters together. Therefore, it is possible to distinguish between temperature effects and real damage events. Experimental data of the I-40 Bridge validates the algorithm. Four levels of damage were gradually introduced to this bridge, later processing of the experimental data revealed that the ambient temperature effect played a mayor role in the variation of the modal parameters. Results show that the proposed algorithm is able to detect the experimental damage despite the temperature variations.

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