Diagnose Expert System of Engine Based on Fuzzy Neural Network

Abstract:

Article Preview

Engine has a high chance of failure, it usually accounts for about 40% of vehicle failures. Study expert system of engine fault diagnosises that it can locate fault timely and accurately, and enhance efficiency. However, the traditional expert system has shortcomings so as inefficient inference and poor self-learning capability. The fuzzy logic and traditional neural networks are combined to form fuzzy neural networks, they are established a model of fuzzy neural network (FNN) of fault diagnosis, and that the model is applied to engine fault diagnosis, complementary advantages, to effectively enhance efficiency of inference and self-learning ability, its performance is higher than the traditional BP network.

Info:

Periodical:

Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim

Pages:

1472-1475

Citation:

M. Tian, "Diagnose Expert System of Engine Based on Fuzzy Neural Network", Advanced Materials Research, Vols. 588-589, pp. 1472-1475, 2012

Online since:

November 2012

Authors:

Export:

Price:

$38.00

[1] Hou Lihua, Zhu Xiaoyan. Fuzzy Reasoning Algorithm in FMS Fault Diagnosis and Maintenance System, Beijing University of Technology, 2000, 20 (3): 281-285.

[2] Xiaomin, Chenyang, Yao Shouguang, Jiang Lei. The Gas Turbine based on Fuzzy Neural Network Fault Diagnosis Expert System Research, Jiangsu Science and Technology University, 2009, 8.

[3] Luo Rongfu, Shao Huihe. Fuzzy Neural Network Method in the Application of Inferential Control, Intelligent Control and Intelligent Automation, Science Press, pp: 763-769.