@inproceedings{d2de604527de4fefb7aea8f6d57f06d9,
title = "State Evaluation of Large Ships Diesel Engine Based on SOM Neural Network",
abstract = "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.",
keywords = "diesel engine, ship, SOM neural network, state assessment",
author = "Jinxin Zhao and Jian Zhou and Peng Shang and Pengpeng Liu and Youlin Xu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 16th IEEE International Conference on Mechatronics and Automation, ICMA 2019 ; Conference date: 04-08-2019 Through 07-08-2019",
year = "2019",
month = aug,
doi = "10.1109/ICMA.2019.8816637",
language = "英语",
series = "Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2036--2040",
booktitle = "Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019",
}
