基于ANN的ESPCP系统转子转速调控技术研究

转子转速是影响螺杆泵寿命的关键。其关联制约因素取决于工况所涉及的物理及化学条件,包括螺杆泵两端的压差、原油的粘度、温度、含砂量、油气比、油水比等。以这些参数作为原始输入,通过两层神经网络确定转子转速与其关联影响因素之间的非线性映射关系,并设计基于人工神经网络的在线转子调速系统。采用这种控制方法有效地延缓了螺杆泵橡胶定子的磨损,保持了较高的容积效率,延长了其使用寿命,同时使螺杆泵的运行具有良好的稳定性、控制灵活性和控制精度。

Research of Rotor Speed Regulating Technology of ESPCP System Based on ANN

The key factor affecting life of progressing cavity pumping system is the rotor speed. The associated constraints depends on the physical and chemical conditions including pressure difference between the pump＇s suction end and the neck of well, oil viscosity, temperature, sand content, gas-oil ratio and oil-water ratio, etc. Taken these parameters as original inputs, the nonlinear mapping relationship between rotor＇s rotational speed and its affecting factors are determined by means of two-layer neural network. With such ANN-based online rotor speed regulating system, the wear of rubber stator has been slowed down, a high volumetric efficiency has been maintained, and the life span extended. At the same time, stable running conditions were obtained, flexibility and precision of control were improved.