基于泵送频率谐波幅值累加和的钻井泵液力端凡尔体故障诊断方法
Fault Diagnosis Method for Hydraulic End of Drilling Pump Valve Based on Harmonic Amplitude Summation of Pump Stroke Frequency
李喆仁 1刘志亮 1廖飞龙 2王文权 3高原 3王皓 3莫巍1
作者信息
- 1. 电子科技大学机械与电气工程学院,成都 611731
- 2. 电子科技大学机械与电气工程学院,成都 611731;中国石油集团川庆钻探工程有限公司安全环保质量监督检测研究院,四川德阳 618300
- 3. 中国石油集团川庆钻探工程有限公司安全环保质量监督检测研究院,四川德阳 618300
- 折叠
摘要
针对钻井泵液力端的凡尔体故障诊断问题,提出了基于泵送频率谐波幅值累加和的钻井泵液力端凡尔体故障诊断方法.首先,设计实验以探究BW-250型钻井泵液力端振动信号的组成成分,通过使用高通滤波器去除低频干扰并保留液力端阀门部件的高频冲击,再采用包络分析和最大相关峭度解卷积方法提取并增强泵阀冲击信号.在钻井现场投入使用的F-800、F-1600HL型号钻井泵上进行故障实验,应用泵送频率谐波幅值累加和指标进行诊断,并与其他振动指标进行对比.结果表明:该方法对于钻井泵凡尔体故障诊断的准确率为 95.79%,相较于均方根(RMS)指标诊断准确率提升 18%以上,相较于裕度、峭度等指标诊断准确率提升 10%以上.该方法为钻井泵阀门凡尔体部件的故障诊断提供了有效的解决思路.
Abstract
Aiming at the problem of fault diagnosis of valve assemblies in the hydraulic end of drilling pumps,a diagnosis methode based on the harmonic amplitude summation of pump stroke frequency was proposed.Initially,experiments were designed to investigate the components of vibration signals from the hydraulic end of the BW-250 type drilling pump.The low-frequency interference was removed using high-pass filters and the high-frequency impact of the valve components of pump valve was retained.Then the pump valve impact signals were then extracted and enhanced by using envelope analysis and maximum correlated kurtosis deconvolution techniques.Fault experiments were conducted on F-800 and F-1600HL drilling pumps in actual drilling sites.The sum of pump stroke frequency harmonic amplitudes was used as a diagnostic index and compared with other vibration indices.The results indicate that this method enables a 95.79%accuracy for fault diagnosis of drilling pump valve assemblies,which is more than 18%higher than that of the root mean square(RMS)index,and more than 10%higher than that of margin and kurtosis indices.The method provides an effective and viable solution for fault diagnosis in drilling pump valve assemblies.
关键词
往复式钻井泵/最大相关峭度解卷积/泵送频率/故障诊断Key words
reciprocating drilling pumps/maximum correlated kurtosis deconvolution/pump stroke frequency/fault diagnosis引用本文复制引用
基金项目
国家自然科学基金(52475091)
四川省科技计划项目(2024JDHJ0057)
出版年
2024
NETL
NSTL
万方数据