DocumentCode
3777348
Title
Artificial intelligence and learning techniques in intelligent fault diagnosis
Author
Sun Yuanyuan; Guo Lili; Wang Yongming
Author_Institution
Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094 China
Volume
1
fYear
2015
Firstpage
702
Lastpage
707
Abstract
At present, based on computer and information technology, intelligent diagnosis technology is in rapid development. In this paper, the application of artificial intelligence and learning techniques in intelligent fault diagnosis are demonstrated, such as Rule-Based Reasoning, Case-based Reasoning, Network neural, Fuzzy Logic, Genetic algorithm, Rough set theory, Bayesian network theory, Multi-agents, Reinforcement Learning, Support Vector Machine. Some kinds of applications are introduced. These intelligent fault diagnosis methods are widely used in complex fault diagnosis system. We will try to use them in our future intelligent fault diagnosis system for space station.
Keywords
"Fault diagnosis","Genetic algorithms","Bayes methods","Cognition","Artificial neural networks","Biological neural networks","Fuzzy logic"
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2015 4th International Conference on
Type
conf
DOI
10.1109/ICCSNT.2015.7490841
Filename
7490841
Link To Document