Condition assessment is an indispensable monitoring step in marine electric propulsion, and is also fundamental in automatic control and condition based maintenance. Recognizing the shortcomings of slow convergence of the intelligent neural-network as well as local optimization, a new method of condition assessment of marine electric propulsion system using support vector machine SVM is applied in this paper. It determined the kernel function and classification method. Using training sampling and K-multiple principal component analysis to optimize the parameters of the kernel function, it obtained a model of condition assessment compatible with SVM. Simulation using MATLAB shows that it can provide high precision and is suitable for generalization as well as improving ship safety.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Condition Assessment of Marine Electric Propulsion System Using Support Vector Machine


    Contributors:

    Conference:

    Second International Conference on Transportation Information and Safety ; 2013 ; Wuhan, China


    Published in:

    ICTIS 2013 ; 2156-2163


    Publication date :

    2013-06-11




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    ELECTRIC MARINE PROPULSION SYSTEM

    CARTER JOHN | European Patent Office | 2025

    Free access

    ELECTRIC MARINE PROPULSION SYSTEM

    TAYLOR BRAD E / REICHARDT DOUGLAS D / PICKETT II PETER A | European Patent Office | 2024

    Free access

    Electric marine propulsion system

    European Patent Office | 2023

    Free access

    Fuzzy neural network in condition maintenance for marine electric propulsion system

    Liang, Shutian / Yang, Junfei / Wang, Yanan et al. | IEEE | 2014


    Electric marine propulsion

    Engineering Index Backfile | 1918