Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7691
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dc.contributor.authorPankaj, A.C.-
dc.contributor.authorShivaprasad, M.V.-
dc.contributor.authorMurigendrappa, S.M.-
dc.date.accessioned2020-03-30T10:02:39Z-
dc.date.available2020-03-30T10:02:39Z-
dc.date.issued2017-
dc.identifier.citationInternational Journal of Acoustics and Vibrations, 2017, Vol.22, 2, pp.242-251en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7691-
dc.description.abstractVibration-based damage detection has been frequently used for low frequency problems. However, there are situations where the damage, like connections of structures with spot welds, mainly affects the highest modes. Energybased approaches such as Statistical Energy Analysis (SEA) is one of the most widely used methods for high frequency analysis that is well-suited for periodic structures. The present work studies the damage detection of joints based on statistical energy analysis-like principles using apparent coupling factors to predict velocity/acceleration responses and detect damage in the spot welds located at various positions on a sub-system (spot-welded plate configurations). Apparent coupling factors have been derived for four cases of spot-welded plates and used further to predict the velocity/acceleration responses using the statistical energy analysis like (SEAL) approach for an assembly of three subsystems (three plates lap joined by spot-welds) for all the possible combinations. The results are discussed, compared, and validated by experimentation and finite element simulations for a healthy and damaged configuration. A database of the predicted values using the SEAL approach for the remaining combinations has been compared with values obtained from finite element simulations. The proposed SEAL-based approach can be effectively applied as a simulation tool to locate the damaged joint in an assembly of subsystems for future use.en_US
dc.titleDetection of damage in spot welded joints using a statistical energy analysis-like approachen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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