潜油电泵智能节电装置的研制

Design of smart on-load tap-changer transformer for oil-immersed pump

在进入高含水期的油田开发中,潜油电泵得到广泛应用,而如何提高其采油系统效率,降低电泵采油井耗电量,成为油田节能减排工作的重点。本文设计了一种新型智能潜油电泵有载调压变压器,给出了结构组成及工作流程,进行了室内外的现场实验,结果表明,该装置可以有效地选择最佳电压,节电效果显著。

The method of combining chaos and RBF neural network can take full advantages of the randomness,initial value sensitivity and so on of chaos,it can also make full use of the large-scale parallel processing,self-organization and adaptive capability of RBF neural networks.Therefore,the RBF neural network with the characteristics of chaos becomes the favorite of many researchers.In this paper,Chaotic RBF neural networks analysis theory and method are researched, these chaotic RBF neural networks are achieved by using the learning,approaching capacity of RBF neural network and the parameters such as the embedded dimension and the delay of chaotic time series,the typical chaotic sequence and modeling forecast of chaotic RBF neural network are simulated.Furthermore,RBF network is applied to electrical loads prediction.The results show that the proposed model has advantages of short prediction time,High-precision for forecasting,etc,having a high significance and value.