Adaptive false discovery rate for wavelet denoising of pavement continuous deflection measurements

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dc.contributor.author Katicha, Samer W.
dc.contributor.author Loulizi, Amara
dc.contributor.author El Khoury, John
dc.contributor.author Flintsch, Gerardo
dc.date.accessioned 2019-09-18T12:52:57Z
dc.date.available 2019-09-18T12:52:57Z
dc.date.copyright 2016 en_US
dc.date.issued 2019-09-18
dc.identifier.issn 1943-5487 en_US
dc.identifier.uri http://hdl.handle.net/10725/11321
dc.description.abstract The traffic speed deflectometer (TSD) is a device used to evaluate the pavement’s structural condition. Measurements obtained from the TSD are affected by noise, which can make it hard to interpret test results. The main objective of this paper is to develop a denoising methodology to use with TSD measurements and improve pavement structural evaluation. The denoising methodology comprises a computational algorithm to identify significant features in a high-dimensional vector of observations containing white Gaussian noise. The algorithm minimizes the classification error of features in the wavelet transform domain by adaptively selecting the level at which to control the false discovery rate. When tested in a simulation study, the results of the proposed algorithm compared favorably with other state-of-the-art methods. The proposed methodology was then successfully used with TSD measurements to identify possible weak joints in a jointed concrete pavement overlaid with an asphalt layer and to calculate asphalt layer modulus values. Repeated measurements were used to validate that the denoised measurements more accurately represent the structural condition than raw measurements. en_US
dc.language.iso en en_US
dc.title Adaptive false discovery rate for wavelet denoising of pavement continuous deflection measurements en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SOE en_US
dc.author.idnumber 200103005 en_US
dc.author.department Civil Engineering en_US
dc.description.embargo N/A en_US
dc.relation.journal Journal of Computing in Civil Engineering en_US
dc.journal.volume 31 en_US
dc.journal.issue 2 en_US
dc.article.pages 04016049-1-04016049-10 en_US
dc.identifier.doi https://doi.org/10.1061/(ASCE)CP.1943-5487.0000603 en_US
dc.identifier.ctation Katicha, S. W., Loulizi, A., Khoury, J. E., & Flintsch, G. W. (2016). Adaptive False Discovery Rate for Wavelet Denoising of Pavement Continuous Deflection Measurements. Journal of Computing in Civil Engineering, 31(2), 04016049. en_US
dc.author.email john.khoury@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ascelibrary.org/doi/full/10.1061/%28ASCE%29CP.1943-5487.0000603 en_US
dc.orcid.id https://orcid.org/0000-0001-7260-2834 en_US
dc.author.affiliation Lebanese American University en_US

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