Multivariate Screening of the Weather Effect on Timber Bridge Movements
Antal upphovsmän: 32016 (Engelska)Ingår i: BioResources, ISSN 1930-2126, E-ISSN 1930-2126, Vol. 11, nr 4, s. 8890-8899Artikel i tidskrift (Refereegranskat) 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.
Ort, förlag, år, upplaga, sidor
2016. Vol. 11, nr 4, s. 8890-8899
Nationell ämneskategori
Annan maskinteknik
Forskningsämne
Träteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-7218DOI: 10.15376/biores.11.4.8890-8899ISI: 000391801300058Scopus ID: 2-s2.0-85046163639Lokalt ID: 58c8f6c1-1179-4252-9da2-f01a1369859bOAI: oai:DiVA.org:ltu-7218DiVA, id: diva2:980107
Anmärkning
Validerad; 2017; Nivå 2; 2017-02-10 (andbra)
2016-09-292016-09-292021-12-13Bibliografiskt granskad