水基动力无杆抽油机故障敏感因子提取方法研究

发布时间：2018-05-22 09:22

  本文选题：抽油机系统 + 特征参数　； 参考：《自动化技术与应用》2016年10期

【摘要】：水基动力无杆抽油机作为一项新技术,尚未大规模的投入使用,对其故障的研究还不成熟。为了提高抽油机系统故障信号的可分性和诊断正确率,针对抽油机的典型故障,对采集到的故障信号进行数据归一化处理以及EEMD降噪。研究了基于时频域特征参数提取的方法以及基于流形学习的降维故障诊断方法。最后提出采用距离差异度和流形差异度寻找故障的敏感因子。研究结果表明,此种方法能够提取抽油机故障的敏感因子,为后续的研究奠定了基础。
[Abstract]:As a new technology, water-based rod-less pumping unit has not been put into use on a large scale. In order to improve the separability and diagnostic accuracy of fault signals in pumping unit system, the collected fault signals are normalized by data normalization and EEMD noise reduction is carried out in view of typical faults of pumping units. The method of feature parameter extraction in time and frequency domain and the method of dimensionality reduction fault diagnosis based on manifold learning are studied. Finally, the sensitivity factors for fault detection by distance difference and manifold difference are proposed. The results show that this method can extract the sensitive factors of pumping unit fault, and lay a foundation for further research.
【作者单位】： 北京信息科技大学机电工程学院;
【基金】：北京市教委科研计划重点项目(编号KZ201311232036)
【分类号】：TE933.1
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本文编号：1921496