石油学报 ›› 2008, Vol. 29 ›› Issue (4): 619-624.DOI: 10.7623/syxb200804029

• 石油工程 • 上一篇    下一篇

示功图频谱分析新方法

何岩峰1, 吴晓东2, 韩国庆2, 肖伟2, 李伟超2, 于晓玲1   

  1. 1. 江苏工业学院机械与能源工程学院, 江苏常州, 213016;
    2. 中国石油大学石油工程教育部重点实验室, 北京, 102249
  • 收稿日期:2007-09-16 修回日期:2007-11-15 出版日期:2008-07-25 发布日期:2010-05-21
  • 作者简介:何岩峰,男,1973年8月生,2008年获中国石油大学(北京)石油天然气学院博士学位,现为江苏工业学院讲师,主要从事采油工程理论与技术方面的教学与科研工作.E-mail:heyanfeng2007@yahoo.com.cn
  • 基金资助:
    国家自然科学基金项目(No.50674096)资助.

Frequency spectrum analysis method for recognition of dynamometer card

HE Yanfeng1, WU Xiaodong2, HAN Guoqing2, XIAO Wei2, LI Weichao2, YU Xiaoling1   

  1. 1. Department of Mechanical and Energy Engineering, Jiangsu Polytechnic University, Changzhou 213016, China;
    2. Key Laboratory for Petroleum Engineering of the Ministry of Education, China University of Petroleum, Beijing 102249, China
  • Received:2007-09-16 Revised:2007-11-15 Online:2008-07-25 Published:2010-05-21

摘要: 示功图分析法是目前常用的抽油井故障诊断方法.由于受到复杂的井下工况的影响,示功图时域信号往往会出现极大变形,从而令示功图分析结果出现错误.为解决这一问题,对示功图时域信号进行了频谱分析.利用将时域信号转换为频域信号的方法,研究了各种频率的能量分布及信号的规律性.分析了示功图频谱的影响因素以及典型工况频谱特征,建立了示功图模糊数学识别模型,并给出了示功图频谱分析方法的步骤.用40多口油井示功图进行了验证,结果表明,频谱分析新方法可用于示功图的识别.

关键词: 示功图, 信号识别, 频谱分析, 抽油井, 故障诊断

Abstract: The dynamometer card analysis is a popular method for diagnosis of failure in pumping wells.However,the complicated bottom-hole conditions often lead to distortion of dynamometer cards and wrong recognition results.A new recognition method was developed and thus the time domain signals were transferred into the frequency domain signals.The distribution of energy at different frequency and the rules of signals were analyzed.The affecting factors and typical characteristics of operating conditions for frequency spectrum of dynamometer cards were discussed.A new fuzzy mathematical recognition model was established and its procedure was developed.The method was used to recognize the behaviors of more than 40 wells.The result shows that the method is applicable to analyze the dynamometer cards.

Key words: dynamometer card, signal recognition, frequency spectrum analysis, pumping well, failure diagnosis

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