@inproceedings{1d8441b8b0cb4abe93b11042edea45f7,
title = "Application of expert system fuzzy BP neural network in fault diagnosis of piston engine",
abstract = "Due to the limitation of BP neural network in fault diagnosis, an improved fault diagnosis method based on Expert System, Fuzzy Theory and improved BP neural network is presented in this paper. And then it is applied in the fault diagnosis of one piston engine. Firstly, a fault database of the piston engine is established by using Expert System, Secondly, the fault symptom is pre-processed with Fuzzy Theory to obtain training samples for neural network, in the end, simulations of fault diagnosis based on BP neural network and improved BP neural network are accomplished by employing the MATLAB software. The simulation results indicate that this method maintains fast convergence, high diagnostic accuracy and it can diagnosis engine failure effectively.",
keywords = "BP neural network, Expert System, Fuzzy Theory, fault diagnosis, piston engine",
author = "Quan Zhang and Nanyu Chen and Jun Huang and Zhijun Meng",
year = "2012",
doi = "10.1109/ICCSEE.2012.170",
language = "英语",
isbn = "9780769546476",
series = "Proceedings - 2012 International Conference on Computer Science and Electronics Engineering, ICCSEE 2012",
pages = "604--607",
booktitle = "Proceedings - 2012 International Conference on Computer Science and Electronics Engineering, ICCSEE 2012",
note = "2012 International Conference on Computer Science and Electronics Engineering, ICCSEE 2012 ; Conference date: 23-03-2012 Through 25-03-2012",
}