Please use this identifier to cite or link to this item: https://doi.org/10.1117/12.814991
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dc.titleStructural damage detection using wireless sensors accounting for data loss
dc.contributor.authorQuek, S.T.
dc.contributor.authorTran, V.A.
dc.contributor.authorDuan, W.H.
dc.contributor.authorHou, X.Y.
dc.date.accessioned2014-06-19T05:52:12Z
dc.date.available2014-06-19T05:52:12Z
dc.date.issued2009
dc.identifier.citationQuek, S.T.,Tran, V.A.,Duan, W.H.,Hou, X.Y. (2009). Structural damage detection using wireless sensors accounting for data loss. Proceedings of SPIE - The International Society for Optical Engineering 7292 (PART 1) : -. ScholarBank@NUS Repository. <a href="https://doi.org/10.1117/12.814991" target="_blank">https://doi.org/10.1117/12.814991</a>
dc.identifier.isbn9780819475527
dc.identifier.issn0277786X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/74376
dc.description.abstractThis paper addresses the issue of intermittent data loss during transmission of wireless network sensors and the application of the reconstruction signal for damage detection with the damage locating vector (DLV) method. The algorithm makes use of frequencies which contribute significant amount of energy in the signal based on Fourier transform. As the amplitudes are uncertain due to lost data, the Fourier amplitudes are estimated based on least-square fit of only the measured portions of the signal. The lost portions are reconstructed through inverse Fourier transform. The procedure is iterated until the discrepancy between estimated lost portions of two consecutive iterations is below a set threshold. This threshold and the power spectral threshold to demarcate the significant frequencies are selected based on results from numerically simulated signals. The reconstructed signals are used with the DLV method for damage detection to investigate the practicality of this procedure. A cantilever truss structure with a pre-stressed cable was monitored using six wireless sensors. The pre-stressed cable was cut mid-way during random load application and data collection. The results obtained support the use of the reconstructed signal within the framework of the DLV method. © 2009 SPIE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1117/12.814991
dc.sourceScopus
dc.subjectDamage locating vector
dc.subjectLost data reconstruction
dc.subjectStructural damage detection
dc.subjectWireless sensors
dc.typeConference Paper
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1117/12.814991
dc.description.sourcetitleProceedings of SPIE - The International Society for Optical Engineering
dc.description.volume7292
dc.description.issuePART 1
dc.description.page-
dc.description.codenPSISD
dc.identifier.isiutNOT_IN_WOS
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