回转支承的故障监测诊断技术研究  

Monitoring and diagnosis technique on slewing bearing

作　　者：刘志军[1] 陈捷[1] 

机构地区：[1]南京工业大学机械与动力工程学院,南京210009

出　　处：《现代制造工程》2011年第11期127-131,共5页Modern Manufacturing Engineering

基　　金：安徽省科技攻关项目(0801020115);江苏省教育厅产业化推进项目(JH09-12)

摘　　要：回转支承的故障监测诊断技术的研究对于提高设备的运行效率、减少经济损失具有重要的意义。有针对性地概述了基于振动信号、温度信号、摩擦力矩、声发射、应力波的回转支承监测诊断技术,以及针对上述信号的分析处理方法,其中包括针对回转支承局部缺陷信号诊断的HHT、EEMD-MSPCA等方法。最后,对各监测诊断方法进行比较,并提出基于混合智能多传感器信息融合技术将成为回转支承故障诊断的重要发展方向。Fault monitoring and diagnosis technology would be a great significance for equipment efficiency and reducing the economic loss due to the slewing bearing failure. Slewing bearing monitoring and diagnosis technique based on vibration, temperature, friction torque, acoustic emission, stress wave were introduced, including the methods of signal processing, especially Hilbert-Huang Transform （HHT）, Ensemble Empirical Mode Decomposition-Based Muhiscale Principal Component Analysis （EEMD-MSPCA） for local fault signal processing were detailed described, At last, various methods were compared and the intelligent sensor fusion technology of slewing bearing fault diagnosis was forecasted to be a important development direction.

关 键 词：回转支承 故障监测 故障诊断 

分 类 号：TH17[机械工程—机械制造及自动化]