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.
Highlights
C racks often occur in structural members and cause serious structural pathologies or even structural collapse
The purpose of this paper is to use additional masses associated with wavelet transform in the processing of non-stationary signals and apply this methodology in experimental done in commercial profiles of steel beams under support conditions close to real situations
The damage can be detected observing the peaks of the Discrete Wavelet Transformation (DWT) of the signal representing the variation of the fundamental frequency vs. the Added Mass Positions (AMP)
Summary
C racks often occur in structural members and cause serious structural pathologies or even structural collapse. It is not possible to visually identify cracks when the structure surface is covered, insulated or located in unreachable locations. To overcome these difficulties, numerical/computational techniques have been under development [2, 3], enabling quick decision-making process concerning the minimization or elimination of damages. A recent research on the technical literature shows that many damage identification algorithms were developed using dynamic characteristics, especially in the frequency domain [5]. In general these techniques uses comparisons between the intact and damaged response of the structure. The purpose of this paper is to use additional masses associated with wavelet transform in the processing of non-stationary signals and apply this methodology in experimental done in commercial profiles of steel beams under support conditions close to real situations
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