| 基于自组织竞争人工神经网络的抽油系统故障诊断 |
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| 引用本文： | 徐芃,徐士进,周会群,尹宏伟. 基于自组织竞争人工神经网络的抽油系统故障诊断[J]. 计算机应用与软件, 2006, 23(4): 48-50 |
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| 作者姓名： | 徐芃 徐士进 周会群 尹宏伟 |
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| 作者单位： | 南京大学地球科学系,江苏,南京,210093;南京大学地球科学系,江苏,南京,210093;南京大学地球科学系,江苏,南京,210093;南京大学地球科学系,江苏,南京,210093 |
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| 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。
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| 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 |
| 收稿时间： | 2004-06-28 |
| 修稿时间： | 2004-06-28 |
APPLICATION OF SELF-ORGANIZING COMPETITION ARTIFICIAL NEURAL NETWORKS IN ROD-PUMPING SYSTEM FAULT DIAGNOSIS |
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| Xu Peng,Xu Shijin,Zhou Huiqun,Yin Hongwei. APPLICATION OF SELF-ORGANIZING COMPETITION ARTIFICIAL NEURAL NETWORKS IN ROD-PUMPING SYSTEM FAULT DIAGNOSIS[J]. Computer Applications and Software, 2006, 23(4): 48-50 |
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| Authors: | Xu Peng Xu Shijin Zhou Huiqun Yin Hongwei |
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| Affiliation: | Department of Earth Sciences, Nanjing University, Nanjing Jiangsu 210093, China |
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| Abstract: | 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. |
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| Keywords: | Self-organizing competition artificial neural network Fault diagnosis Rod-pumping system Dynamometer card Pattern recognition |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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