Structural health monitoring of constrained tapered beam-like structures using natural frequencies and nodal points
Wang, Le, Waters, T.P. and Yang, Zhichun (2011) Structural health monitoring of constrained tapered beam-like structures using natural frequencies and nodal points. [in special issue: 9th International Conference on Damage Assessment of Structures (DAMAS 2011) 11–13 July 2011, St Anne's College, University of Oxford] Journal of Physics: Conference Series, 305, (1), 012067-[9pp]. (doi:10.1088/1742-6596/305/1/012067).
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The integrity and safety of beam-like structures are dependent in part on their boundary conditions which can vary with time due to damage or aging. Structural health monitoring of such structures should therefore include attention to boundary conditions. Where the boundary conditions can be represented by a lumped spring then the identification of associated stiffness parameter values may be a means to quantifying the integrity of the support. This paper investigates such a method for identifying the equivalent translational and rotational stiffness of a constrained tapered beam-like structure. An analytical model of a beam of tapered width and thickness is adopted as a simplified representation of a tower-like structure. The model is used to explore in what scenarios natural frequencies and/or nodal points might be sufficiently sensitive to changes in support conditions to be measurable indicators of damage. The method is evaluated by Monte Carlo simulations for a numerical example where the severity of noise can be controlled.
|Digital Object Identifier (DOI):||doi:10.1088/1742-6596/305/1/012067|
|Additional Information:||Item 012067|
|Subjects:||T Technology > TA Engineering (General). Civil engineering (General)|
|Divisions :||Faculty of Engineering and the Environment > Institute of Sound and Vibration Research > Dynamics Research Group
|Accepted Date and Publication Date:||
|Date Deposited:||07 Nov 2011 16:35|
|Last Modified:||31 Mar 2016 13:46|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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