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Probability distribution of decay rate: a statistical time-domain damping parameter for structural damage identification
This article proposes a novel vibration-based damage identification method, named the probability distribution of decay rate. By introducing a statistical framework, the probability distribution of decay rate method estimates the damage-induced changes in overall damping behaviour of a free-vibratio...
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Published in: | Structural health monitoring 2019-01, Vol.18 (1), p.66-86 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This article proposes a novel vibration-based damage identification method, named the probability distribution of decay rate. By introducing a statistical framework, the probability distribution of decay rate method estimates the damage-induced changes in overall damping behaviour of a free-vibration dynamic system. Utilising free-vibration impulse response data, a one-dimensional data set of local maxima–minima points is constructed. A statistical analysis of this data set is then performed to derive damage-sensitive parameters. It is demonstrated that through the use of a statistical analysis framework, a number of enhancements are attained in terms of both robustness and leniency in estimating the significantly nonlinear property of overall damping. An impact hammer test is conducted in the laboratory to verify the efficacy of the proposed probability distribution of decay rate method. The test was performed on a scale-model steel Warren-truss bridge structure, subjected to bolt-connection failures. The comparison results between the probability distribution of decay rate method and the standard experimental modal analysis method confirm that the former is effective for damage identification of complex structures, particularly with real experimental data and steel-frame structure assemblies. |
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ISSN: | 1475-9217 1741-3168 |
DOI: | 10.1177/1475921718817336 |