Abstract
It is necessary to switch the control strategies for propulsion system frequently according to the changes of sea states in order to ensure the stability and safety of the navigation. Therefore, identifying the current sea state timely and effectively is of great significance to ensure ship safety. To this end, a reasoning model that is based on maximum likelihood evidential reasoning (MAKER) rule is developed to identify the propeller ventilation type, and the result is used as the basis for the sea states identification. Firstly, a data-driven MAKER model is constructed, which fully considers the interdependence between the input features. Secondly, the genetic algorithm (GA) is used to optimize the parameters of the MAKER model in order to improve the evaluation accuracy. Finally, a simulation is built to obtain experimental data to train the MAKER model, and the validity of the model is verified. The results show that the intelligent sea state identification model that is based on the MAKER rule can identify the propeller ventilation type more accurately, and finally realize intelligent identification of sea states.
Highlights
In recent years, marine electric propulsion technology has become more and more mature, and marine electric propulsion system has been widely used in ships with the rapid development of power electronic technology [1,2]
This paper proposes an intelligent sea states identification model based on the maximum likelihood evidential reasoning (MAKER) rule to identify the current sea state effectively and choose the suitable control strategy for propulsion system
An identification model of ventilation based on the MAKER rule is established to identify the ventilation type first, and the sea state is identified based on the correspondence between the type of propeller ventilation and sea states
Summary
Marine electric propulsion technology has become more and more mature, and marine electric propulsion system has been widely used in ships with the rapid development of power electronic technology [1,2]. Smogeli et al [8,9,10,11] conducted a series of simulation experiments and control strategy researches on the ventilation generated by the propeller under extreme sea conditions and proposed a propeller torque loss estimation method that was based on empirical formulas to realize the identification of propeller ventilation and determine the type of sea state. The main contributions of this work are as follows: (1) in this paper, an intelligent sea states identification model based on MAKER rule is established, which can identify the ventilation of propeller and the sea state more accurately.
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