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Ship motion prediction method based on time-frequency analysis and BP neural network

A BP neural network and ship motion technology, applied in the field of ship motion forecasting, can solve problems such as motion nonlinearity and randomness that make research difficult, and achieve the effects of shortened preparation time, accurate fitting model, and high resolution

Active Publication Date: 2014-02-12
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In practice, it is of great value to predict the movement of ships, but the nonlinearity and randomness of the movement bring difficulties to the research

Method used

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  • Ship motion prediction method based on time-frequency analysis and BP neural network
  • Ship motion prediction method based on time-frequency analysis and BP neural network
  • Ship motion prediction method based on time-frequency analysis and BP neural network

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Embodiment 1

[0028] Such as figure 1 Shown, the present invention is a kind of ship motion prediction method based on time-frequency analysis and BP neural network, and its steps are as follows:

[0029] (1) Use the ship motion simulator to obtain the simulation data of the ship motion. The sampling frequency of the simulation data is 50 Hz, and a total of 50 s of data is collected. figure 2 Obtain simulated data of the ship's motion for the simulator. Depend on figure 2 It can be seen that the ship motion data contains periodic motion and noise of multiple frequencies. The nonlinear model of ship motion is constructed as follows:

[0030] Y=A 1 ×sin(ω 1 ×t+B 1 )+A 2 ×sin(ω 2 ×t+B 2 )+W (1)

[0031] Among them, Y is the amplitude of the ship motion, A 1 is the amplitude of the main periodic motion, ω 1 is the frequency of the main periodic motion, B 1 is the phase of the main periodic motion, A 2 is the magnitude of the secondary periodic motion, ω 2 is the frequency of th...

Embodiment 2

[0044] The present invention is used to carry out ship motion prediction experiments on 5 groups of ship motion simulation data. Table 2 is the standard deviation of ship motion forecast. It can be seen that the present invention has better prediction accuracy of ship motion under different ship motion conditions.

[0045] Table 2 is the experimental verification effect (m) of the present invention

[0046]

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Abstract

The invention discloses a ship motion prediction method based on time-frequency analysis and a BP neural network. The ship motion prediction method includes the first step of carrying out data sampling on ship motion by using a ship motion sensor, the second step of using a Marple method in autoregressive (AR) spectral analysis to obtain main periodic motion component of ship motion, the third step of using a wavelet analysis method in time-domain analysis to carry out analysis and pre-processing on original data of ship motion and decomposing the original data to obtain a trend term and a noise term of ship motion, and the fourth step of using the BP neural network to fit the trend term to obtain a nonlinear motion model of a ship through fitting, and accordingly providing short-term ship motion prediction. The ship motion prediction method completely meets the requirements of engineering application for real-time performance, and has important significance in studying ship motion predication methods under different sea conditions.

Description

technical field [0001] The invention relates to a ship motion prediction method, which is suitable for short-term motion prediction and system application on ships, and in particular to a ship motion prediction method based on time-frequency analysis and BP neural network. Background technique [0002] The purpose of this subject research is to explore a new forecast method to describe the ship attitude motion under high sea conditions, and provide technical support for the real-time adaptive control of the ship and its equipment motion attitude by analyzing its motion law. [0003] When a ship is sailing at sea, it will produce six degrees of freedom swaying motion when disturbed by waves. Due to the complex and changeable conditions of the actual sea waves, the motion of the ship is also very complicated, and the motions of each degree of freedom are coupled with each other to form a complex nonlinear system. In practice, it is of great value to predict the motion of ship...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08
Inventor 王玮丁振兴孟跃王蕾张谦
Owner BEIHANG UNIV
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