An Intelligent Fault Diagnostics for Turbine Generator by Modified Neural Model

Author

Weng, Pin-Hsuan ; Yang, Jen-Pin ; Liu, Fang-Tsung ; Huang, Huang-Chu ; Yu, Ker-Wei ; Hwang, Rey-Chue

Author_Institution

Electr. Eng. Dept., I-Shou Univ., Kaohsiung

fYear

2008

fDate

18-20 June 2008

Firstpage

296

Lastpage

296

Abstract

In this paper, an intelligent fault diagnostic tool for oil-fired power plant with turbine generator by using the modified neural network was proposed. This tool is able to monitor the running condition of power plant immediately. It also can reveal the fault situation if the power plant had some troubles. Therefore, such a well designed mechanism can be used as the training tool for laboratory course in power turbine studies. To demonstrate the feasibility of the tool we developed, several real case studies were simulated. From the simulation results shown, the tool we developed is very promising in the real applications.

Keywords

fault diagnosis; neural nets; power engineering computing; steam power stations; turbogenerators; intelligent fault diagnostic tool; neural model; oil-fired power plants; turbine generators; Fault detection; Fault diagnosis; Intelligent networks; Learning systems; Neural networks; Neurons; Power engineering and energy; Power generation; Signal processing; Turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on

Conference_Location

Dalian, Liaoning

Print_ISBN

978-0-7695-3161-8

Electronic_ISBN

978-0-7695-3161-8

Type

conf

DOI

10.1109/ICICIC.2008.151

Filename

4603485