Network turbo unit monitoring system based on advanced diagnostic strategies

Author

Zhang, Yong ; Wang, Ning-Ling

Author_Institution

North China Electr. Power Univ., Baoding, China

Volume

6

fYear

2004

fDate

26-29 Aug. 2004

Firstpage

3449

Abstract

It is a trend to detect and analyze the faults of turbo-generator unit by means of advanced diagnostic theory and open network structure. A turbo-unit fault diagnosis system for shaft monitoring based on the improved RBF neural network diagnostic model is introduced in this paper, by which the typical faults and some new-type ones are to be diagnosed directly, besides it is of the function of modifying the samples continuously. More importantly, an open Browser/Server network structure is proposed to realize the operating condition information sharing among the levels of equipment managers, production managers and remote experts.

Keywords

computerised monitoring; fault diagnosis; power engineering computing; radial basis function networks; turbogenerators; RBF neural network diagnostic model; advanced diagnostic strategies; advanced diagnostic theory; fault diagnosis system; network turbo unit monitoring system; open network structure; shaft monitoring; turbo-generator unit; Data acquisition; Databases; Fault diagnosis; Information analysis; Monitoring; Network servers; Power system management; Shafts; Signal analysis; Web server;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on

Print_ISBN

0-7803-8403-2

Type

conf

DOI

10.1109/ICMLC.2004.1380383

Filename

1380383