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2024 | OriginalPaper | Buchkapitel

Research on the Method of Inverting Indicator Diagram with Electrical Parameters of Pumping Unit Based on Neural Network

verfasst von : Qiao-ling Dong, Chun-long Sun, Chao Gao, Zhen-chao Guo, Cui Wang, Lu-fang Zhou, Xing Qi, Chun-hong Li, Hai-qun Yu, Feng Wei

Erschienen in: Proceedings of the International Field Exploration and Development Conference 2023

Verlag: Springer Nature Singapore

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Abstract

In view of the problems that the load cell used to test the indicator diagram in the pumping unit is easy to drift in the long term and needs manual regular maintenance, a new method is proposed to demonstrate the indicator diagram of the electrical parameters in the pumping unit well. By combining neural network and big data analysis technology, BP neural network model is established to carry out learning、training and simulation analysis on the historical data of pumping unit, to find the corresponding relationship between electrical parameters and indicator diagram, and to realize the direct conversion of indicator diagram using electrical parameters. After145 field tests, the accuracy of electrical parameter inversion diagram based on neural network reaches 93.2%. This method has the advantages of low model complexity, fast operation speed and high accuracy, which provides a new way to obtain the indicator diagram of pumping unit well, and has great significance for the digital construction of pumping unit well.

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Metadaten
Titel
Research on the Method of Inverting Indicator Diagram with Electrical Parameters of Pumping Unit Based on Neural Network
verfasst von
Qiao-ling Dong
Chun-long Sun
Chao Gao
Zhen-chao Guo
Cui Wang
Lu-fang Zhou
Xing Qi
Chun-hong Li
Hai-qun Yu
Feng Wei
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-97-0272-5_23