基于时域指标的滚动轴承故障特征提取方法  

The Method Based on the Time Domain Indexes of Rolling Bearing Fault Feature Extraction

作　　者：薛小庆[1] 陈博[1] 刘婷[1] Xue Xiaoqing;Chen Bo;Liu Ting(Physics and Electronic Engineering Department,Xianyang Normal University,Xianyang Shaanxi,712000)

机构地区：[1]咸阳师范学院物理与电子工程学院,陕西咸阳712000

出　　处：《电子测试》2018年第23期58-60,共3页Electronic Test

基　　金：咸阳师范学院"青年骨干教师"(XSYGG201605);陕西省重点研发计划项目(2018NY-158);咸阳市科学技术研究计划项目(2015k02-05)

摘　　要：为了实时监测滚动轴承是否发生故障,对振动信号进行实时采样,按一定周期对不同故障状态和同一故障不同损伤直径的状态提取时域指标特征值。通过实验表明,该方法能有效的降低数据维数,准确地监测滚动轴承的故障状态。Forreal-time monitoring rolling bearing failure state,the method makes real-time sampling of vibration signals and extracts feature of the time domain indexes in a certain period for different fault state and different damage of the diameter of the same fault of the state. Experiments show that the method can reduce the dimension of data and monitor the state of rolling bearing fault accurately.

关 键 词：滚动轴承 时域指标特征值 故障状态 

分 类 号：TH133.33[机械工程—机械制造及自动化]