Abstract
System identification is used in location detection, target tracking, prediction in oil markets and so on. In this paper, the Kalman Filter (extended) technique is explored in monitoring the health of a jacket structure, in a stochastic excited wave environment. Hydrodynamic coefficients drag (CD) and inertia (CM), usually experimentally obtained, are important parameters to assess the force on a structure using the Morison’s equation. Usually these coefficients appearing in the force equation are un-known for majority of the slender offshore structures and are a priori obtained using some set of prototype experiments as these parameters depend on lot of factors (Keulegan-Carpenter number, roughness, dimensions and so on). Therefore, the recourse to parameter identification techniques based on Kalman filtering can be an alternative.
In this paper, the problem is analysed using Airy wave theory where a cylinder is assumed to be fixed at the seabed. Numerical analysis is done to create experimental conditions to observe the dynamic response of the system. These numerical results are then plagued with white noise to represent the observations from experiments. These measurements are subsequently used in identification of the drag and inertia coefficients for the cylinder. This is presently attempted using the Extended Kalman Filter technique.
With the use of this model the Extended Kalman Filter is shown to be able to identify time varying drag and inertia coefficients of the cylinder problem. For the present case, measurement sensors are placed for the measured force, along with the motions: velocity and acceleration. The above method can easily be implemented in jacket structures or similar offshore structures for attention due to increase in forces owing to marine growth.
