改进的邻域相关法在回转支承故障诊断中的应用
|
摘要
回转支承具有运行速度低、旋转方向和旋转角度多变、承载能力高、工作环境复杂等特点,为保证生产作业顺利进行,对回转支承进行故障诊断非常必要。文中对现场回转支承3种运行阶段的振动信号进行采集,利用去均值方法对信号降噪处理,采用改进的邻域相关法进行故障诊断和分类,通过模拟和实际数据验证了方法的可行性,为回转支承故障诊断提供参考。
The slewing bearing has the characteristics of low running speed, changeable rotating direction and angle, high bearing capacity and complex working environment. In order to ensure the smooth operation of production, it is very necessary to carry out fault diagnosis on the slewing bearing. In this paper, the vibration signals of the three operation stages of the slewing bearing are collected, the signal is denoised by the de-averaging method, and the fault diagnosis and classification are carried out by the improved neighborhood correlation method. The feasibility of the method is verified by simulation and actual data, which provides a reference for the fault diagnosis of the slewing bearing.
The slewing bearing has the characteristics of low running speed, changeable rotating direction and angle, high bearing capacity and complex working environment. In order to ensure the smooth operation of production, it is very necessary to carry out fault diagnosis on the slewing bearing. In this paper, the vibration signals of the three operation stages of the slewing bearing are collected, the signal is denoised by the de-averaging method, and the fault diagnosis and classification are carried out by the improved neighborhood correlation method. The feasibility of the method is verified by simulation and actual data, which provides a reference for the fault diagnosis of the slewing bearing.
引文
[1] Wang Fengtao,Liu Chenxi,Su Wensheng,et al.Condition monitoring and fault diagnosis methods for low-speed and heavy-load slewing bearings:a literature review[J].Journal ofViboengineering,2017,19(5):3 429-3 443.
[2]苏文胜,薛志钢,李云飞.门座起重机回转支承故障诊断[J].起重运输机械,2017(6):82-86.
[3] Yi B.K,Faloutsos.C.Fast time sequence indexing for arbitrary Lp Norms[EB/OL].[2015-12-14]. http://repository.cmu.edu/compsci/553/.
[4] Wahyu Caesarendra,Buyung Kosasih,Anh Kiet Tieu,et al.Circular domain features based condition monitoringfor low speed slewing.com bearing[J].Mechanical Systems and Signal Processing,2014,45:114-138.
[5]苏文胜.滚动轴承信号处理及特征提取方法研究[D].大连:大连理工大学,2010.
[2]苏文胜,薛志钢,李云飞.门座起重机回转支承故障诊断[J].起重运输机械,2017(6):82-86.
[3] Yi B.K,Faloutsos.C.Fast time sequence indexing for arbitrary Lp Norms[EB/OL].[2015-12-14]. http://repository.cmu.edu/compsci/553/.
[4] Wahyu Caesarendra,Buyung Kosasih,Anh Kiet Tieu,et al.Circular domain features based condition monitoringfor low speed slewing.com bearing[J].Mechanical Systems and Signal Processing,2014,45:114-138.
[5]苏文胜.滚动轴承信号处理及特征提取方法研究[D].大连:大连理工大学,2010.