The Application of Visualization and Neural Network Techniques in a Power Transformer Condition Monitoring System

Authors:
Zhi-Hua Zhou;Yuan Jiang;Xu-Ri Yin;Shi-Fu Chen
Affiliations:
-;-;-;-
Venue:
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Year:
2002

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Abstract

In this paper, visualization and neural network techniques are applied together to a power transformer condition monitoring system. Through visualizing the data from the chromatogram of oil-dissolved gases by 2-D and/or 3-D graphs, the potential failures of the power transformers become easy to be identified. Through employing some specific neural network techniques, the data from the chromatogram of oildissolved gases as well as those from the electrical inspections can be effectively analyzed. Experiments show that the described system works quite well in condition monitoring of power transformers.