DocumentCode
2999660
Title
Beam-pumping unit energy-saving control system based on support vector machine
Author
Gao, Meijuan ; Tian, Jingwen ; Zhou, Shiru ; Zhang, Fan
fYear
2008
fDate
1-3 Sept. 2008
Firstpage
1864
Lastpage
1869
Abstract
Considering the issues that the energy saving process for beam-pumping unit is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The support vector machine (SVM) has the ability of strong nonlinear function approach, it has the ability of strong generalization and it also has the feature of global optimization. In this paper, an intelligent energy-saving control system of beam-pumping unit based on regression SVM is presented. Moreover, we propose a self-adaptive parameter adjust iterative algorithm to confirm SVM parameters. The parameters of energy-saving control process of beam-pumping unit are measured using multi sensors, and then the control system can control the working state of beam-pumping unit real-time. The system is used in the oil recovery plant. The experimental results prove that this system is feasible and effective.
Keywords
generalisation (artificial intelligence); iterative methods; nonlinear control systems; petroleum industry; production engineering computing; pumps; regression analysis; support vector machines; beam-pumping unit; complicated system; global optimization; intelligent energy-saving control system; multisensors; nonlinear function approach; nonlinear system; oil recovery plant; regression support vector machine; self-adaptive parameter adjust iterative algorithm; strong generalization; Control systems; Energy measurement; Intelligent control; Intelligent sensors; Intelligent systems; Iterative algorithms; Machine intelligence; Nonlinear systems; Process control; Support vector machines; Beam-pumping unit; Energy-saving control; Support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-2502-0
Electronic_ISBN
978-1-4244-2503-7
Type
conf
DOI
10.1109/ICAL.2008.4636462
Filename
4636462
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