Ruichao Zhang1,*, Liqiang Wang1, Dechun Chen2
Energy Engineering, Vol.118, No.4, pp. 1069-1082, 2021, DOI:10.32604/EE.2021.014961
Abstract In recent years, deep learning models represented by convolutional neural networks have shown incomparable advantages in image recognition and have been widely used in various fields. In the diagnosis of sucker-rod pump working conditions, due to the lack of a large-scale dynamometer card data set, the advantages of a deep convolutional neural network are not well reflected, and its application is limited. Therefore, this paper proposes an intelligent diagnosis method of the working conditions in sucker-rod pump wells based on transfer learning, which is used to solve the problem of too few samples in a dynamometer card data set. Based… More >
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