摘要
泥浆泵是钻井作业的关键设备。它的可靠性直接影响钻井效率和安全。针对泥浆泵故障诊断难度大、精度低的问题,提出一种基于高频分析的快速诊断方法。通过构建多通道高频振动信号采集系统,设计自适应滤波算法提取特征频段,融合时频域特征构建故障特征向量,采用支持向量机实现故障分类。实际应用表明,该方法显著提高了故障检出率和定位精度,为泥浆泵预防性维护提供了有效技术支持。
The mud pump is a key piece of equipment in drilling operations.Its reliability directly affects drilling efficiency and safety.To address the challenges of high difficulty and low accuracy in mud-pump fault diagnosis,a fast diagnostic method based on high-frequency analysis is proposed.A multi-channel high-frequency vibration-signal acquisition system is constructed,and an adaptive filtering algorithm is designed to extract characteristic frequency bands.Time-and frequency-domain features are then fused to build a fault-feature vector,and a support vector machine is used for fault classification.Practical application shows that this method significantly improves fault detection rate and localization accuracy,providing effective technical support for preventive maintenance of mud pumps.
作者
安海亮
AN Hailiang(China Oilfield Services Limited,Tianjin 300450)
出处
《现代制造技术与装备》
2025年第12期165-167,共3页
Modern Manufacturing Technology and Equipment
关键词
高频振动
自适应滤波
支持向量机
时频特征融合
high-frequency vibration
adaptive filtering algorithm
support vector machine
feature fusion
