摘要
抽油系统的故障诊断技术一直是采油工程的一个重要研究课题。本文将自组织竞争神经网络应用于抽油系统的故障诊断中来实现示功图的自动聚类。自组织竞争神经网络具有良好的可训练性和分类能力,理想的泛化性能,是一种快速有效的分类方法,可用于抽油系统故障的实时诊断。
Fault diagnosis of rod-pumping system is an important subject of oil extraction research. The self-organizing competition artificial neural network is used to classify dynamometer cards fault diagnosis of rod-pumping system. This technique has good trained properties, excellent classification capability and generalization capability. It is a fast and effective classifying method, applicable to the real time fault diagnosis of rod-pumping system.
出处
《计算机应用与软件》
CSCD
北大核心
2006年第4期48-50,共3页
Computer Applications and Software
关键词
自组织竞争人工神经网络
故障诊断
有杆抽油系统
示功图
模式识别
Self-organizing competition artificial neural network Fault diagnosis Rod-pumping system Dynamometer card Pattern recognition
