Prediction method for dissolved gas concentration in transformer oil based on long and short-term memory network
A long-short-term memory and transformer oil technology, applied in instruments, measuring devices, scientific instruments, etc., can solve problems such as slow convergence speed, inability to predict and analyze dissolved gas concentration in time, long cycle, etc., and achieve the effect of reducing the probability of failure
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[0062] Under normal operation of the power transformer, due to the aging of the internal insulating solid, a small amount of gas will be dissolved in the insulating oil, mainly hydrogen (H 2 ), methane (CH 4 ), ethane (C 2 H 6 ), ethylene (C 2 H 4 ), acetylene (C 2 H 2 ), carbon monoxide (CO), carbon dioxide (CO 2 ) And other gases. The different operating conditions of the transformer can be distinguished according to the ratio of the dissolved gas content in the oil, for example: hydrogen H during high-energy discharge 2 And acetylene C 2 H 2 The content of hydrocarbon gas will increase; in the case of a strong magnetic field, the content of hydrocarbon gas will increase and show a certain correlation. The present invention chooses hydrogen (H 2 ), methane (CH 4 ), ethane (C 2 H 6 ), ethylene (C 2 H 4 ), acetylene (C 2 H 2 ), carbon monoxide (CO), carbon dioxide (CO 2 ) And other 7 kinds of gases are used as characteristic parameters.
[0063] For the prediction o...
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