Research on fault sample knowledge abstraction and fault fuzzy diagnosis for large power station halving-style condenser

Author

Liangyu, Ma ; Bingshu, Wang ; Yongguang, Ma ; Jianqiang, Gao ; Zhensheng, Tong

Author_Institution

Res. Inst. of Simulation & Control, North China Electr. Power Univ., China

Volume

1

fYear

2000

fDate

2000

Firstpage

351

Abstract

Typical fault sample knowledge library of the halving style condenser is abstracted and completed based on the dynamic simulation model of halving-style condenser developed by the authors. The fuzzy pattern recognition is used to realize halving-style condenser fault diagnosis. A new kind of subordinate function is given to overcome the demerit of one old function. Diagnostic effects of the two different functions are compared by example

Keywords

condensers (steam plant); fault diagnosis; fuzzy set theory; knowledge acquisition; pattern recognition; power engineering computing; steam power stations; diagnostic effects; dynamic simulation model; fault fuzzy diagnosis; fault sample knowledge abstraction; fuzzy pattern recognition; power station halving-style condenser; subordinate function; Cooling; Equations; Erbium; Fault diagnosis; Heat transfer; Libraries; Pattern recognition; Power generation; Temperature; Water heating;

fLanguage

English

Publisher

ieee

Conference_Titel

Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on

Conference_Location

Perth, WA

Print_ISBN

0-7803-6338-8

Type

conf

DOI

10.1109/ICPST.2000.900082

Filename

900082