Modal parameter estimation from ambient vibration measurements of a dam using stochastic subspace identification methods

Author(s): P. Bukenya, P. Moyo, C. Oosthuizen
Paper category: Conference
Book title: Concrete Repair, Rehabilitation and Retrofitting III (ICCRRR)
Editor(s): M.G. Alexander, H.-D. Beushausen, F. Dehn, P. Moyo
Print ISBN: 978-0-415-89952-9
Publisher: Taylor & Francis Group
Pages: 237 - 238
Total Pages: 2
Language: English

Dynamic testing of concrete dams under ambient vibration excitations such as wind and water waves has advantages such as no artificial excitations is required which makes it a cheaper option. It also tests the structure in its operation conditions so there are no interruptions. In ambient vibration testing, only output responses from the structure are used in modal parameter identification. Stochastic Subspace Identification (SSI) algorithm is the state of art technique in modal parameter estimation for civil engineering structures. This paper evaluates the performance of three SSI algorithms namely; unweighted principal component, principal component and canonical variate analysis in the identification of modal parameters (natural frequencies and damping ratios) of a Roode Elsberg Dam in South Africa. It is demonstrated that all the three algorithms are close to each other in estimating natural frequencies but not damping ratios. Natural frequencies estimated by the SSI algorithms are compared with the FEM results and it is shown that they did not pick some modes.

Online publication: 2014
Publication Type: abstract_only
Public price (Euros): 0.00