Deformation monitoring using different least squares adjustment methods: A simulated study
2016 (English)In: KSCE Journal of Civil Engineering, ISSN 1226-7988, E-ISSN 1976-3808, Vol. 20, no 2, 855-862 p.Article in journal (Refereed) Published
This study aims to investigate the ability of different least squares adjustment techniques for detecting deformation. A simulated geodetic netwo rk is used for this purpose. The observations are collected using the Total Station instrument in three epochs and different least squares adjustment methods are used to analyze the simulated network. The applied methods are adjustment-byelement, using variance-covariance components and Tikhonov regularization. For numerical computation, we utilized exist geodetic network around the simulated network and the deformation (changes in the simulated network) imposes to the object using a simulator in each epoch. The obtained results demonstrate that more accurate outcome for detection of small deformation is possible by estimating variance-covariance components. The difference of the estimated and the simulated deformations in the best scenario, i.e., applying variance-covariance components, is 0.2 and 0.1 mm in x and y directions. In comparison with adjustment by element and Tikhonov regularization methods the differences are 1.1 and 0.1 in x direction and 1.4 and 1.1 mm in y direction, respectively. In addition, it is also possible to model the deformation and therefore it can be seen that how the calculated displacement will affect the result of deformation modelling. It has been demonstrated that determining reasonable variance-covariance components is very important to estimate realistic deformation model and monitoring the geodetic networks.
Place, publisher, year, edition, pages
Springer, 2016. Vol. 20, no 2, 855-862 p.
deformation detection, least squares adjustment, regularization and variance component, Deformation, Geodesy, Reactor cores, Deformation monitoring, Least squares adjustments, Numerical computations, Realistic deformations, Tikhonov regularization, Tikhonov regularization method, Variance components, Least squares approximations
IdentifiersURN: urn:nbn:se:kth:diva-177226DOI: 10.1007/s12205-015-0454-5ISI: 000372243800036ScopusID: 2-s2.0-84958045334OAI: oai:DiVA.org:kth-177226DiVA: diva2:873924
QC 201511252015-11-252015-11-172016-04-18Bibliographically approved