State Evaluation of Large Ships Diesel Engine Based on SOM Neural Network

被引:0
作者
Zhao, Jinxin [1 ]
Zhou, Jian [1 ]
Shang, Peng [1 ,2 ]
Liu, Pengpeng [3 ]
Xu, Youlin [3 ]
机构
[1] Xi An Jiao Tong Univ, Sch Mech Engn, Xian, Shaanxi, Peoples R China
[2] Engn Univ PAP, Sch Equipment Management & Support, Xian, Shaanxi, Peoples R China
[3] Naval Res Acad, Beijing 100161, Peoples R China
来源
2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA) | 2019年
关键词
SOM neural network; diesel engine; state assessment; ship;
D O I
10.1109/icma.2019.8816637
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
There is still no fixed evaluation method for the state evaluation of large-scale ships diesel engines. Here, the SOM self-organizing map neural network model is applied to judge and evaluate the state of the marine diesel engine. Firstly, according to the basic functions and structure of the diesel engine, the selection and establishment of scientific indicators should be carried out on the principle of evaluating indicators. Then, after the selected state indicator parameters are normalized, the data is input to the SOM neural network for training, and finally use the trained network to evaluate the state of the input parameters. The trained SOM neural network can effectively improve the evaluation efficiency and reduce the influence of some subjective factors, and the experimental results show that the model is feasible in the state evaluation of Marine diesel engines.
引用
收藏
页码:2036 / 2040
页数:5
相关论文
共 18 条
  • [1] Cao L. H., 2015, INT C EL AUT MECH EN
  • [2] CHEN Ling, 2006, Ship & Ocean Engineering, V35, P22
  • [3] CHEN. Y. G., 2012, ACTA AERONAUTICA AST, V34, P104
  • [4] A performance degradation evaluation method for a turbocharger in a diesel engine
    Cui, Xinjie
    Yang, Chuanlei
    Serrano, Jose Ramon
    Shi, Mingwei
    [J]. ROYAL SOCIETY OPEN SCIENCE, 2018, 5 (11):
  • [5] THE SELF-ORGANIZING MAP
    KOHONEN, T
    [J]. PROCEEDINGS OF THE IEEE, 1990, 78 (09) : 1464 - 1480
  • [6] LIU B.Y., 2005, VEHICLE ENGINE, P17
  • [7] [刘伊凡 Liu Yifan], 2018, [内燃机学报, Transactions of Csice], V36, P182
  • [8] Diesel engine condition monitoring using a multi-net neural network system with nonintrusive sensors
    Porteiro, Jacobo
    Collazo, Joaquin
    Patino, David
    Luis Miguez, Jose
    [J]. APPLIED THERMAL ENGINEERING, 2011, 31 (17-18) : 4097 - 4105
  • [9] [曲晓慧 Qu Xiaohui], 2005, [兵工学报, Acta Armamentarii], V26, P557
  • [10] WANG X. R., 2018, EQUIPMENT MANUFACTUR, V278, P131