Open AccessDesign of diesel engine fault prediction system based on MATLAB
Author(s) -
Wei Liu,
Yu Gao,
Ning Chen,
Zhimin Wang
Publication year - 2020
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 - 10.1088/1742-6596/1654/1/012072
Subject(s) - combing , artificial neural network , fault (geology) , diesel engine , matlab , bearing (navigation) , computer science , block (permutation group theory) , automotive engineering , cylinder block , position (finance) , diesel fuel , engineering , artificial intelligence , geometry , cartography , mathematics , finance , seismology , geology , economics , geography , operating system
For the fault of main bearing wear of diesel engine, this paper puts forward the idea of combing artificial neural network and bearing wear warning system together. Selecting RBF neural network calculating fast as a research tool, diesel cross-head slide block working as the research object, we make the related systems. When the position of the slider changes due to wear, the sensor which monitors the position can immediately transmit the fault data to neural networks, after calculation, the neural network put the fault type out, to search the place of the failure. This method is of high accuracy, fast speed, and the results suggest clear.