Abstract
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 wavelet neural network has the ability of strong nonlinear function approach, adaptive learning, fast convergence and global optimization. In this paper, an energy-saving control system of beam-pumping unit based on wavelet neural network is presented. We adopt a method of reduce the number of the wavelet basic function by analysis the sparse property of sample data, and use the learning algorithm based on gradient descent to train network. The parameters of energy-saving control process of beam-pumping unit are measured using multi sensors. 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.
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