Abstract:
This essay introduces and analyzes the dissolved gases in the insulating oil of power
transformers. Analysis of soluble and free gas is one of the most commonly used
troubleshooting methods for detecting and evaluating equipment damage. Although the
analysis of oil-soluble gases is often complex, it should be expertly processed during
maintenance operation. The destruction of the transformer oil will produce some
hydrocarbon type gases. The development of this index is based on two examples of
traditional evaluation algorithms along with fuzzy logic inference engine. Through
simulation process, the results of the initial fractures in the transformer are obtained in
two ways by the "Duval Triangle" and "Rogers ratios". In continue, three digit codes
containing the fault information are created based on the fuzzy logic inference engine to
achieve better results and eliminate ambiguous zones in common methods especially in
Duval Triangle method. The proposed method is applied to 80 real transformers to
diagnose the fault by analyzing the dissolved oil based on fuzzy logic. The results
illustrate the proficiency of this new proposed algorithm. Finally, with utilization of a
neural network the new practical inference function is derived to make the algorithm
more usable in online condition monitoring.
