Open AccessResearch on fault warning of marine diesel engine cooling system based on Deep Belief Network
Author(s) -
Qian Ye,
Yunsheng Liu,
Chaoyou Guo,
Chenyang Ao,
Tao Guan,
Zhe Xu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1750/1/012066
Subject(s) - diesel engine , deep belief network , fault (geology) , artificial neural network , diesel fuel , deep learning , warning system , automotive engineering , water cooling , artificial intelligence , computer science , engineering , marine engineering , real time computing , mechanical engineering , aerospace engineering , geology , seismology
With the development of artificial intelligence and big data technology, deep learning has been applied to fault warning and diagnosis. In this paper, the typical failure modes of marine diesel engine cooling system are analyzed, and the characteristic parameters are selected. The fault warning model is established based on the deep belief neural network (DBN). The training and testing of the model are carried out by using the experiment data of a marine diesel engine. The results show that the deep belief neural network can effectively realize the fault warning of marine diesel engine cooling system.