摘要
针对旋转机械故障诊断中准确提取故障特征的问题,论文研究了基于振动信号特征的故障分析方法,综合利用时域和频域分析技术对采集的振动信号进行处理与分析。通过均方根值、峭度指标等时域参数和频率成分、幅值等频域参数的提取,结合振动信号采集与预处理,成功识别了齿轮泵的齿轮故障。结果表明,该方法能有效提取故障特征,实现早期故障预警与诊断。此研究为旋转机械的故障诊断提供了一种高效、准确的技术手段,对保障设备安全稳定运行具有重要意义。
Addressing the issue of accurately extracting fault characteristics in the diagnosis of rotating machinery faults,this paper studies a fault analysis method based on vibration signal characteristics.It comprehensively utilizes time-domain and frequen⁃cy-domain analysis techniques to process and analyze the collected vibration signals.By extracting time-domain parameters such as root mean square values and kurtosis indicators,as well as frequency-domain parameters such as frequency components and ampli⁃tudes,combined with the collection and preprocessing of vibration signals,the gear faults of the gear pump are successfully identi⁃fied.The results show that this method can effectively extract fault features,achieving early fault warning and diagnosis.This re⁃search provides an efficient and accurate technical means for the fault diagnosis of rotating machinery,which is of great significance for ensuring the safe and stable operation of equipment.
作者
孙洋
李则龙
季朋
SUN Yang LI Zelong;JI Peng(China Coast Guard Academy,Ningbo 315801)
出处
《舰船电子工程》
2025年第10期141-145,共5页
Ship Electronic Engineering
基金
2023年度科研项目(编号:WJJY23JL0342)资助。
关键词
旋转机械
故障分析
振动信号
特征提取
rotating machinery
fault analysis
vibration signal
feature extraction
