Title :
Oil Fault Diagnosis Based on Fuzzy Rough Set Theory and Bayesian Network
Author :
Liu Yan ; Li Shi-qi ; Fu Yan
Author_Institution :
Sch. of Mech. Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan
Abstract :
This paper proposes a new method of information fusion of oil fault diagnosis. Firstly a fuzzy decision information system is established using fuzzy processing of oil monitoring data. Aiming at the problem that rough set can not be directly applied to the data with continuous variable, this paper adopts the method of fuzzy information system knowledge discovery to the reduction of attributes, which can avoid the information loss by discretizating continuous attribute values in rough set theory. Then based on the connection between the fault symptoms of diesel and oil monitoring data, this paper constructs a Bayesian diagnosis network with the topological structure being used to express the qualitative knowledge and the probability distributions of the nodes in the network to solve the uncertainty of the knowledge. Finally, an example proves that the great significance that information fusion is used in the field of oil monitoring.
Keywords :
condition monitoring; data mining; fault diagnosis; fuzzy set theory; lubricating oils; mechanical engineering computing; rough set theory; Bayesian Network; Bayesian diagnosis network; fuzzy decision information system; fuzzy rough set theory; information fusion; information loss; knowledge discovery; oil fault diagnosis; oil monitoring data; probability distributions; rough set theory; topological structure; Bayesian methods; Fault diagnosis; Fuzzy set theory; Fuzzy systems; Information systems; Monitoring; Petroleum; Probability distribution; Set theory; Uncertainty; Bayesian network; fuzzy rough sets; information fusion; oil fault diagnosis;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3391-9
Electronic_ISBN :
978-0-7695-3391-9
DOI :
10.1109/ICINIS.2008.76