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

fYear

2008

fDate

13-15 Dec. 2008

Firstpage

319

Lastpage

323

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICACIA.2008.4770033

Filename

4770033