On a fault detection system based on neuro-fuzzy fusion method

Author

Xu, Ye ; Wang, Zhuo

Author_Institution

Coll. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China

fYear

2010

fDate

26-28 May 2010

Firstpage

3190

Lastpage

3193

Abstract

A fault detection system of a power plant by means of neuro-fuzzy fusion method is discussed in this paper. Stator temperature together with temperature variations of refrigerant at the entrance and exit of hydrogenerator group are firstly monitored by temperature sensors. The fuzzy system of the aforementioned variables and their membership functions, next, are designed according to expertise knowledge base. Finally, a neuron-fuzzy fusion model is generated by merge the fuzzy system into a neural networks fusion model, and it is proved to be efficient with a correctness ratio of 91% by testing experiments on around one third of overall samples.

Keywords

fault diagnosis; fuzzy neural nets; hydroelectric power stations; power engineering computing; sensor fusion; temperature sensors; fault detection system; hydrogenerator group; membership functions; neural networks fusion model; neuro-fuzzy fusion method; neuron-fuzzy fusion model; power plant; stator temperature; temperature sensors; Fault detection; Fusion power generation; Fuzzy systems; Neural networks; Power generation; Refrigerants; Stators; System testing; Temperature measurement; Temperature sensors; fault detection; fuzzy logic; membership function; neuro-fuzzy fusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5498631

Filename

5498631