A Transformer Fault Diagnosis Method Based on Bayesian Network
A technology for transformer faults and diagnosis methods, applied in the directions of instruments, measuring electrical variables, measuring devices, etc., can solve the problems of transformer faults without considering the connection and inapplicable fault factors, so as to improve maintenance efficiency, reduce operating costs, and quickly and accurately diagnose. Effect
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[0029] The invention is based on the real-time operation data of transformers accumulated by Yunnan power grid, and further explains the invention and the effectiveness of the invention in combination with the accompanying drawings. Refer to attached figure 1 The process of establishing Bayesian network model based on fault data is shown, and the steps of establishing Bayesian model for transformer fault diagnosis are described in detail.
[0030] Step 1 Clarify the transformer faults that can be diagnosed by dissolved gas in transformer oil. According to the fact that the common faults of Yunnan Power Grid Company, determine the fault set as medium temperature overheating (300-700) ℃, low temperature overheating (below 150 ℃), low temperature overheating (150 ~300) ℃, low-energy discharge and overheating, the attached table 1 shows the transformer fault data. The hydrogen, methane, acetylene, ethylene, ethane, total hydrocarbon, carbon monoxide, carbon dioxide and other gas ...
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