Fault Diagnosis of Generator Based on D-S Evidence Theory

Authors:
Qingdong Du;Jin Li;Xiao Chen
Affiliations:
-;-;-
Venue:
ISDA '08 Proceedings of the 2008 Eighth International Conference on Intelligent Systems Design and Applications - Volume 01
Year:
2008

Citing 0
Cited 1

Evidence-Based Combination of Weighted Classifiers Approach for Epileptic Seizure Detection using EEG Signals

International Journal of Knowledge Discovery in Bioinformatics

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Abstract

It is difficult to identify the fault type with the signal gathered from the sensors. In this paper, a new fusion algorithm based on the Dempster-Shafer theory of evidence and neural networks is brought forward. This method combines the advantages of D-S evidence theory and the BP neural network. Neural networks are used to pretreated the data gathered from the embedded sensors in the monitoring system of hydropower plant. Compared with the approaches that only adopt D-S evidence theory or neural networks, the accuracy of diagnostic results is obviously improved, and the signals analysis proved this conclusion. This method has been applied in the monitoring system of JiLin FengMan HydroPower Plant successfully.