Damage identification in beams using additional rove mass and wavelet transform

Abstract

There is a need for efficient techniques that could identify damages in structures such as in bridges, pipelines, buildings, dams, among others. In order to carry out continuous monitoring of structures, this paper proposes a new experimental methodology for the identification of damages in steel beams. The methodology is based on the variation of the fundamental frequencies caused by the application of an extra additional mass along the length of the structure. This paper proposes the association of additional masses with wavelet transform in the processing of non-stationary signals and the realization of experimental tests on commercial profiles of steel beams under support conditions close to real situations. The experimental tests of simply supported steel beams are presented and discussed in this paper. The results show that the proposed methodology can identify damages or at least give a good indication of the region where damages might be.

Beam-like damage detection methodology using wavelet damage ratio and additional roving mass

“…Therefore, for the present analysis, it is sufficient to use 100 finite elements to detect reasonably the damage position in the present cases with a considerable reduction of computational effort. In experimental point of view, Palechor et al [15] carried out the need to apply interpolation methods to increase the amount of data. Experimental data is limited to the number of points that can be measured with available instrumentation.…”

“…Most of the time, the intact response is very difficult to be obtained. Hence, researchers have been testing some techniques using only the damaged response, as [10][11][12][13][14][15][16]. Structural health monitoring (SHM) consists of periodic evaluations, on a full scale, the dynamic behavior of structures using sensors installed in the structural system to detect environmental actions and determine proactive maintenance actions.…”

Model-based and Signal-Based Inverse Methods

“…In 1990, Ingrid Daubechies used Mallat's work to build a set of smooth wavelet orthonormal bases with compact supports. Daubechies' works are the foundation of current Wavelets applications (Palechor et al, 2019;.…”