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Multivariate Screening of the Weather Effect on Timber Bridge Movements
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0002-7076-9494
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0001-8404-7356
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Wood Science and Engineering.ORCID iD: 0000-0001-5872-2792
Number of Authors: 32016 (English)In: BioResources, ISSN 1930-2126, E-ISSN 1930-2126, Vol. 11, no 4, p. 8890-8899Article in journal (Refereed) Published
Abstract [en]

Monitoring displacements and weather impact of complex structures such as a large cable stayed footbridge generates large amount of data. In order to extract, visualize and classify health-monitoring data to get a better comprehension multivariate statistical analysis is a powerful tool. This paper is a screening to evaluate if principal component analysis is useful on health monitoring data. Principal component analysis (PCA) and projections to latent structures by means of partial least squares (PLS) modeling were used to achieve a better understanding of the complex interaction between bridge dynamics and weather effects. The results show that principal component analysis (PCA) give good overview of the collected data, and PLS modeling show that winds from east and west best explain bridge movements.

Place, publisher, year, edition, pages
2016. Vol. 11, no 4, p. 8890-8899
National Category
Other Mechanical Engineering
Research subject
Wood Science and Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-7218DOI: 10.15376/biores.11.4.8890-8899ISI: 000391801300058Local ID: 58c8f6c1-1179-4252-9da2-f01a1369859bOAI: oai:DiVA.org:ltu-7218DiVA, id: diva2:980107
Note

Validerad; 2017; Nivå 2; 2017-02-10 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Björngrim, NiclasHagman, OlleWang, Alice

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