Abstract
Structural health monitoring (SHM) is an important area that ensures the integrity and safety of all structures related to aviation, civil and mechanical engineering. Structural damage greatly affects the dynamic properties of a structure which, in turn, alters its measured dynamic response or vibrational characteristics. Hence, researchers have exploited this relation by devising damage detection techniques that are based on natural frequencies, mode shapes, mode shape curvatures, operational deflection shapes, operational curvature shapes etc. In most of these techniques, presence of damage is ensured with the change in the measured response. The measured response is typically in the form of Frequency Response Functions (FRFs) which requires the information of input data, usually the excitation force. In practice, it is difficult to measure the excitation force in operational areas and particularly, in randomly excited structures. So, in case of unknown excitations the response-only techniques are found useful, as they do not require input information and generate transmissibility functions (TFs) which contain information about damage. Furthermore, the majority of damage detection methods including the response-only techniques require the data of intact structures to distinguish the change due to damage, which in case of existing structures is impractical. To address this issue, smoothing techniques are applied on the available data to get presumed baseline information of undamaged structure. ?In this paper, two response-only techniques namely Operational deflection shape (ODS) FRF and Random Decrement (RanDec) are presented along with a smoothing technique to make the damage detection process baseline-free. To implement this modified approach in a beam-type structure, different damage scenarios are considered. The results of both response-only techniques are compared with those from FRFs and it is shown that RanDec technique gives better results when the record length of response and sampling time was increased.
Keyword(s)
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