石油化工设备技术 ›› 2024, Vol. 45 ›› Issue (1): 49-53.doi: 10.3969/j.issn.1006-8805.2024.01.011

• 状态监测与分析 • 上一篇    下一篇

轴心轨迹特征算法在唐山LNG海水泵故障监测中的应用

雒海隆1,田建坤1,王大林2,李 旭3   

  1. 1. 中石油京唐液化天然气有限公司,河北 唐山 063000;
    2. 清华大学,北京 100095;
    3. 和尘自仪(嘉兴)科技有限公司, 浙江 嘉兴314000
  • 收稿日期:2023-10-09 接受日期:2023-12-31 出版日期:2024-01-09 发布日期:2024-01-09
  • 通讯作者: 王大林 E-mail:luohailong@petrochina.com.cn
  • 作者简介:雒海隆,男,2008年毕业于中国石油大学(华东)油气储运工程专业,学士,长期从事LNG设备设施检维修以及数字化技术应用研究和工程实践工作,高级工程师。

Application of Axis Orbit Feature Algorithm in Fault Monitoring of Tangshan LNG Seawater Pumps

Luo Hailong1, Tian Jiankun1, Wang Daling2, Li Xu3   

  1. 1. PetroChina Jingtang LNG Company Limited, Tangshan, Hebei, 063000;
    2. Tsinghua University, Beijing, 100095;
    3.Hechen Ziyi (Jiaxing) Technology Co., Ltd., Jiaxing, Zhejiang, 314000
  • Received:2023-10-09 Accepted:2023-12-31 Online:2024-01-09 Published:2024-01-09
  • Contact: Wang Dalin E-mail:luohailong@petrochina.com.cn

摘要: 大型泵类故障监测和预警对LNG运行安全具有重要意义。传统的监测手段主要依赖于振动超限报警,但部分故障并不会引发振动超限,且一旦振动超限通常会引发联锁停机,直接影响正常生产。文章针对唐山LNG国产首台套立式长轴海水泵构建了一套基于轴心轨迹特征识别的故障预警算法模型。该算法模型利用现有振动传感器的监测信号,对轴心的分布特征进行训练和识别,并据此构建出正常运行轨迹特征指标,当轴心轨迹特征出现偏离时发出故障报警提示。实践证明,该方法能够更加充分地利用监测数据,实现海水泵故障的早期识别,为减少海水泵非计划停运提供有效支持。

关键词: 海水泵, 轴心轨迹, 特征识别, 故障预警

Abstract: The fault monitoring and early warning of large pumps is significantly important to the safety of LNG operation. Traditional monitoring methods mainly rely on vibration alarm, but some faults will not cause vibration over-limit. And once the vibration exceeds the limit, it will usually cause interlock shutdown, which will directly affect production. In this paper, a fault early warning algorithm model based on axis orbit feature identification was constructed for Tangshan LNG seawater pumps. The monitoring signals of existing vibration sensors were used in the model to analyze the distribution features of the pump axis orbit. Base on this, the normal running feature index was constructed. When the axis orbit index deviates, a fault alarm will be issued to the operator to start an inspection process. Practices have proved that this method can make full use of the monitoring data to achieve early identification of seawater pump failures and provide effective support for reducing unplanned outages of seawater pumps.

Key words: seawater pump, axis orbit, feature recognition, fault early warning