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Wavelet transform-fractal dimension-based methodology for damage assessment in truss type structures

Structural Health Monitoring (SHM) is one of the most interesting research topics into civil engineering field. SHM consists of the processing and interpretation of the acquired data of a structure in order to evaluate its condition. An accurate early damage detection is an important task in SHM, as a reduction of both required time and repairing costs can be achieved. One of the most common damage scenarios that is present in many civil structures is corrosion. It has been shown that a damage condition changes the vibration response of the structure. For this reason, a methodology based on the discrete wavelet transform and fractal dimension, capable of performing an efficient diagnosis of a structure condition using its vibration response, is presented. The proposed methodology is divided in two main steps, where the first one employs the discrete version of the wavelet transform to denoise and decompose the acquired signal; finally, in step 2, it is executed two different algorithms (Box Dimension and Katz) to obtain the fractal dimension (FD) value of decomposed signal, which is used for detection and quantification of damage into structure. The obtained results show that the proposed DWT-FD methodology is efficient for monitoring the structure condition, which is validated using the measured data of a five-bay truss structure under different levels of corrosion damage.