Research On Measurement And Prediction Of Ship Deformation Based On Inertial Technology

The existence of ship deformation is the key factor which affects the naval combat effectiveness at sea.With the development of science and technology,requirements for the accuracy of shipborne armament become much higher,so it is necessary to ensure the unification of the attitude datum of each battle position on the ship.In other words,the measurement of ship deformation must be accurate.In order to realize accurate measurement and estimation of ship deformation in real time,this paper studies the structural ship deformation during navigation.In this paper,the algorithm theory of ship deformation measurement method is deeply studied,and the theoretical analysis and research are focused on the angular velocity matching method,ship deformation modeling and short-term deformation prediction.A set of semi-physical simulation platform was built and the experimental simulation was carried out.The main work of this paper is as follows:The measurement method of angular velocity matching ship deformation based on inertial technology is studied,and the angular velocity matching equation is derived according to two sets of optical fiber inertial navigation systems.By using the angular velocity matching method to measure the equation and data,the static and dynamic deformation are modeled,and the Kalman measurement filter equation is constructed to estimate the deformation angle of the ship.Aiming at the problem that the traditional static deformation model cannot track the slowly varying components,the quasi-static model is derived under the condition of static water equilibrium,and the characteristics of the slowly varying components of the static deformation are analyzed and the parameters are identified.From the mechanical mechanism and data characteristics,the dynamic deformation is deduced to be a second-order Markov process,the parameter are estimated by the least square method in real time,and the problem of parameter estimation misalignment caused by FIR low-pass filter is analyzed and solved.In this paper,the short-term prediction of ship deformation is studied,and a method of short-term deformation prediction based on traditional state dependent autoregression and radial basis neural network is proposed.Based on the measured data obtained by the angular velocity matching method,the prediction model based on rbf-ar is constructed.Experiment results show that this method is superior to the traditional time series method in predicting ship deformation.A computer and a semi-physical simulation platform were built to simulate the measurement of ship deformation under the condition of ship’s navigation sway.