Truss-type designs are widely used in civil structures. Despite the fact that they are robust and reliable structures, different kinds of damage can appear. In order to avoid human and economic losses, the development and application of damage-detection methodologies are paramount. In this work, a methodology based on the empirical mode decomposition (EMD) method and the Shannon Entropy Index (SEI) to detect incipient damages associated with corrosion in a 3D 9-bay truss-type bridge is presented. As different EMD methods are presented in literature, the most representative methods are investigated in order to evaluate their performance for this task. To this end, the vibration signals generated in the truss-type bridge at different conditions are analyzed. For the damage condition, four severity levels of simulated corrosion (1 mm, 3 mm, 5 mm, and 8 mm of diameter reduction) generated into the elements of truss-type bridge are considered. Results demonstrate the effectiveness of the proposal in terms of detecting corrosion in its very early stage (1 mm of reduction in the element).

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During the last years, civil infrastructure has experienced an increasing development to satisfy the society’s demands such as communication, transportation, work and living spaces, among others. In this sense, the development and application of methods to guarantee the structure optimal operation, known as Structural Health Monitoring schemes, are necessary in order to avoid economic and human losses. Modern schemes employ the structure vibration response as any damage will modify the structure physical properties, which will be reflected in the vibration response. Thus, by measuring the waveform changes of the response, the structure condition can be determined. Considering this fact, this paper investigates the effectiveness of Katz fractal dimension, Higuchi fractal dimension, Box fractal dimension, Petrosian fractal dimension, and Sevcik fractal dimension which are nonlinear measurements to extract features of vibration signals in order to determine the health condition of a 3D 9-bay truss-type bridge. The obtained results show that the algorithms corresponding to Higuchi and Petrosian fractal dimension algorithms exceed the other nonlinear measurements in efficiency to discriminate between a healthy structure and a damage produced by corrosion.

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