Abstract
For the information and knowledge in oil-immersed power transformer fault diagnosis is randomness and uncertainty, this paper firstly analyzed the relationship between DGA and the fault categories; and then combined it with adaptive genetic algorithm, and proposed a adaptive genetic algorithm based fault rules intelligent learning model, so the model was used for oil-immersed transformer fault diagnosis. It combined adaptive genetic algorithm, credit evaluation system and experts’ guidance, because of the global search properties of genetic algorithm and the artificial expert prior knowledge, the system will search out the optimality fault rules finally. At last, the experiments also proved that the proposed fault rules intelligent learning mode used in oil-immersed power transformer diagnosis has a high rate of identification for faults.
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Li, Y., Bao, D., Luo, C., Huang, L., Cao, L. (2011). An Intelligent Fault Diagnosis Method for Oil-Immersed Power Transformer Based on Adaptive Genetic Algorithm. In: Lee, G. (eds) Advances in Automation and Robotics, Vol.1. Lecture Notes in Electrical Engineering, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25553-3_21
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DOI: https://doi.org/10.1007/978-3-642-25553-3_21
Publisher Name: Springer, Berlin, Heidelberg
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