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
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"
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2015 4th International Conference on
DOI :
10.1109/ICCSNT.2015.7490841