摘要
为提高风力发电机轴承状态异常判别和故障诊断能力,保证机组可靠稳定运行,降低机组维护成本,发电机轴承采用了振动在线状态监测频谱信号的判别方法,即利用振动数据样本及特征频率分析,监测轴承运行状态。通过对轴承振动数据的分析来评定其运行状态,为轴承故障预判提供依据。
To improve the state anomaly discrimination and fault diagnosis ability of wind generator bearing,guarantee the reliable and stable operation,reduce the maintenance costs, the spectrum signal discriminated method of generator bearing vibration online condition monitoring technology was studied.The vibration data sample and characteristic frequency analysis were used to monitor the running state of the bearing.The bearing operation state was evaluated by analyzing the bearing vibration data,which provides the basis for the bearing failure prediction.
作者
姬相磊
高旭东
杜振东
JI Xiang-lei;GAO Xu-dong;DU Zhen-dong(CSIC Motor Technology Co.,Ltd.,Taiyuan 030000,China)
出处
《微特电机》
2019年第8期74-76,共3页
Small & Special Electrical Machines
关键词
轴承
振动监测
频谱分析
故障诊断
bearing
vibration monitoring
frequency analysis
fault diagnosis
