Research on Intelligent Optimization Control Method for Oil Pumping
Author(s) -
Tian Jingwen,
Gao Meijuan,
Ge Guangshuang
Publication year - 2014
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
ISSN - 1687-8132
DOI - 10.1155/2014/926958
Subject(s) - artificial neural network , wavelet , genetic algorithm , morlet wavelet , energy (signal processing) , optimal control , fitness function , generalization , computer science , intelligent control , engineering , control theory (sociology) , wavelet transform , control (management) , mathematical optimization , artificial intelligence , mathematics , discrete wavelet transform , machine learning , mathematical analysis , statistics
In the oil production process, some oil pumps exist in the light load running and empty pumping problems, which result in the waste of electric energy. In order to realize the oil pumping energy saving optimal control by adopting oil pumping start-stop intermittent control scheme, an intelligent energy saving optimal control system based on genetic algorithm and wavelet neural network is proposed in this paper. The Morlet wavelet is adopted as the activation function of neural network and builds the wavelet neural networkandthe structure and parameters of the wavelet neural network which are chromosome encoded, and the genetic algorithm is used to optimize the connection weights and the scale parameters in order to improve the generalization ability and the approximation ability of neural networks. The parameters of effective oil pumping energy saving optimal control are measured using multisensors. The system is used in the oil production plant; the test data show that the oil pumping energy conservation effect is obvious.
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