Utilization of Kalman Filter Technique in Deformation Prediction of Above Surface Storage Tank

R. Ehigiator-Irughe, M. O. Ehigiator


Kalman filtering is a multiple-input, multiple-output filter that can optimally estimate the states of a system, so it can be considered a suitable means for deformation analysis. The states are all the variables needed to completely describe the system behavior of the deformation process as a function of time (such as position, velocity etc.). The standard Kalman filter estimates the state vector where the measuring process is described by a linear system. While, in order to process a non-linear system an optimized aspect of Kalman filter is appropriate. Engineering Geodesy is the application of only geodetic methods for mapping certain geometric shape or of the topographic surface with respect to accurately define reference frame. Geodetic methods configure positions in Space with respect to the Earth and interpret the geodetic measurements in terms of a Euclidean Geometry. However Geodesy as discipline may unravel not only the geometric but also the kinematical and the physical nature of the Earth via geometric measures. At present, like in  other Earth disciplines, Geodesy measurements depend on the dynamical and physical features of the Earth. One of the main issues of Engineering Geodesy is accurate prediction of value of structural deformation. Above storage Tank is like other deformable structure whose shape, form and safety is of interest to Engineering fields. The main purpose of structural deformation monitoring scheme and analysis is to detect any significant movements of the structure. Presented here is geodetic methods of determination of Velocity and Acceleration of deformable object in Time domain and predict deformation value using Kalman Filter. Analysis of the result indicated that there are correlations between the observed and the predicted deformation value for year 2004, 2008, 2010 and 2012 respectively.

Keywords:  Structural Deformation, Kinematic, Kalman Filter

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ISSN (Paper)2224-719X ISSN (Online)2225-0638

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