基于声音信号的离心泵轴承故障预警研究
Research on early warning of centrifugal pump bearing faults based on acoustic signals
杨俊 1穆伯锋 1张敏 1詹蕊菱 1马谧 1郑通明 1梁陶 1孙德彬 1彭松1
作者信息
- 1. 中国石油西南油气田公司川西北气矿,四川 江油 621700
- 折叠
摘要
为了对离心泵运行状态进行监测,通过采集离心泵运转声音信号,对离心泵声音信号进行时域分析、频域分析,提取时频域轴承故障预警特征.利用变分模态分解方法,筛选合适的本征模态函数进行包络调解,通过包络谱图分析离心泵轴承故障特征信息,提取离心泵轴承故障预警特征.针对离心泵轴承故障预警,从中提取正常运行和轴承故障运行特征参数,建立预警特征,进而实现对离心泵维护和保养的预警,提高离心泵使用寿命,避免离心泵轴承故障.研究结果对离心泵轴承故障预警具有指导意义.
Abstract
To monitor the operational state of centrifugal pump,this study involves the collection and experimental analysis of these signals,analyzing them in both time and frequency domains to extract early warning indicators of bearing faults in the time-frequency domain.The Variational Mode Decomposition method is used to select the appropriate intrinsic mode function for envelope demodulation.This process facilitates the analysis of bearing fault feature information via envelope spectrum,from which early warning indicators for bearing faults are extracted.By extracting characteristic parameters of both normal and faulty bearing operations,this study establishes early warning indicators for centrifugal pump bearing failures.This is crucial for timely maintenance interventions,significantly enhancing the lifespan of centrifugal pumps and preventing industrial operation downtimes due to sudden bearing failures.The study results provide significant reference for the early warning of centrifugal pump bearing faults.
关键词
离心泵/声音信号/时频域分析/变分模态分解/预警特征Key words
Centrifugal pump/Acoustic signal/Time frequency domain analysis/Variational Mode Decomposition/Early warning indicators引用本文复制引用
基金项目
中国石油西南油气田公司川西北气矿科研项目(2023-14)
出版年
2024
国家科技期刊平台
NSTL
万方数据