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- W2766880075 abstract "The traditional power transformer fault judgment is through the oil chromatography online monitoring data set a threshold to determine whether the transformer is faulty, so there is a problem of the correct rate of fault alarm. This paper adopts the data analysis method, based on the Fuzhou transformer oil chromatography and its repair order data, selects effective characterization of influence the characteristics of transformer running state as evaluation indexes. A double-hidden layer BP neural network models were constructed and applied into transformer fault alarm, and evaluation accuracy is higher than the common fault alarm model." @default.
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- W2766880075 date "2017-11-03" @default.
- W2766880075 modified "2023-09-24" @default.
- W2766880075 title "Application of Double-Hidden Layer BP Neural Network in Transformer Fault Alarm" @default.
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- W2766880075 doi "https://doi.org/10.1007/978-3-319-70730-3_20" @default.
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