Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/2266
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dc.contributor.authorKumar, Gaurav-
dc.contributor.authorDhariwal, Sandeep-
dc.contributor.authorKumar, Roshan-
dc.contributor.authorYadav, Arvind R-
dc.contributor.authorAmponsah, Evans-
dc.contributor.authorSingh, Prasanna K-
dc.date.accessioned2023-12-09T08:56:03Z-
dc.date.available2023-12-09T08:56:03Z-
dc.date.issued2022-
dc.identifier.citationpp. 1-5en_US
dc.identifier.isbn9781665442909-
dc.identifier.urihttps://doi.org/10.1109/AISP53593.2022.9760606-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2266-
dc.description.abstractThere is a damage to the health of civil structures over the time due to aging and loading effects i.e., wind,earthquakes etc. To identify these hidden damages at the earliest, some reliable damage detection techniques are required. In addition, it becomes essential to monitor the performance of structural integrity and it results in the increased life span of the structures. In this paper, the average energy entropy scheme based on the discrete wavelet transform is proposed to detect incipient damage in the structures. The measured response is first decomposed into a set of wavelet components and average energy entropy is computed. The proposed method is applied to the simulated response of the beam obtained with different crack levels, and performance is compared to the approximate entropy. The results obtained from the proposed method illustrate a consistent and reliable damage indicator in comparison with the existing method. © 2022 IEEE.en_US
dc.language.isoenen_US
dc.publisher2022 2nd International Conference on Artificial Intelligence and Signal Processing, AISP 2022en_US
dc.subjectDamage detectionen_US
dc.subjectSHMen_US
dc.subjectTime-frequency analysisen_US
dc.subjectWaveleten_US
dc.titleDamage Identification of Beam Structure Using Discrete Wavelet Transformen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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