石油学报 ›› 2006, Vol. 27 ›› Issue (1): 111-113.DOI: 10.7623/syxb200601024

• 石油工程 • 上一篇    下一篇

钻井机械故障诊断数据挖掘系统结构的研究

张允, 张宁生, 刘茜, 宁刚   

  1. 西安石油大学 陕西西安 710065
  • 收稿日期:2005-03-08 修回日期:2005-06-30 出版日期:2006-01-25 发布日期:2010-05-21
  • 作者简介:张允,男,1978年5月生,2002年毕业于西安石油大学机械设计制造及其自动化专业,现为西安石油大学在读硕士,主要研究方向为管理信息系统与计算机网络.E-mail:sdyunzh@163.com
  • 基金资助:
    国家自然科学基金"油气储层损害的信息融合理论与方法研究"(No.50274095)资助.

Data mining system for drilling mechanical failure diagnosis based on neural network

Zhang Yun, Zhang Ningsheng, Lui Qian, Ning Gang   

  1. Xi'an Shiyou University, Xi'an 710065, China
  • Received:2005-03-08 Revised:2005-06-30 Online:2006-01-25 Published:2010-05-21

摘要: 利用数据挖掘技术,研究了复杂的钻井机械故障诊断问题,提出了钻井机械故障诊断数据挖掘系统的结构框架,并对基于神经网络的钻井机械故障诊断进行了分析,给出了钻井机械故障诊断系统连接模型.通过钻井机械故障诊断数据挖掘系统的运用实例,验证了该诊断方法的正确性和实用性.

关键词: 钻井机械;故障诊断;神经网络;数据仓库;数据挖掘技术

Abstract: The complicated failure of drilling machinery was investigated with the data mining technique.The structure frame of the drilling mechanical failure data mining system is presented.The drilling mechanical failure diagnosis based on neural network was analyzed.A new method for making use of neural network to carry out diagnosis of drilling mechanical failure was proposed.The validity and practicability of the new diagnosis method were proved by the application case history of the data mining system for drilling mechanical failure diagnosis.

Key words: drilling machinery, failure diagnosis, neural network, data warehouse, data mining technique

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