Title :
Intelligent Fault Diagnosis System in Large Industrial Networks
Author :
Huang, Yuan-Yuan ; Li, Jian-ping ; Xu, Fu-long ; Tang, Yuan ; Lin, Jie
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
Traditional fault diagnosis system in large industrial networks is not intelligent enough and cannot predict faults. It is too expensive for industrial corporations. This paper brings forward an intelligent fault diagnosis system-IFDS, which uses new types of intelligent database technology, and has the ability of effectively solving the fault diagnosis and prediction issue of current industrial Ethernet network. In addition, this paper discusses some methods which can be implemented in IBM DB2 database.
Keywords :
data mining; data warehouses; decision support systems; fault diagnosis; industrial control; local area networks; DSS; IBM DB2 database; OLAP; data warehouse; fault prediction; intelligent database technology; intelligent fault diagnosis system; large industrial Ethernet network; Application software; Computer industry; Deductive databases; Electrical equipment industry; Electronics industry; Ethernet networks; Fault diagnosis; Industrial control; Intelligent networks; Intelligent systems; CORBA; DSS; Data mining; OLAP; data warehouse;
Conference_Titel :
Apperceiving Computing and Intelligence Analysis, 2008. ICACIA 2008. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3427-5
Electronic_ISBN :
978-1-4244-3426-8
DOI :
10.1109/ICACIA.2008.4770033
