【摘要】 介绍一种将小波去噪与多尺度熵方法相结合的滚动轴承故障诊断方法,通过采用小波去噪后信号进行多尺度熵分析,得到多尺度熵曲线分布,对滚动轴承的正常状态、内圈故障、滚动体故障和外圈故障4种故障类型下的振动信号分析表明,小波多尺度熵方法在合适的尺度因子下能够有效的区分4种故障类型,可以进行滚动轴承的故障识别,并且优于传统的多尺度熵方法。更多还原

【Abstract】 Introduces a method of combining wavelet denoising and multi-scale entropy for rolling bearing fault diagnosis, through the analysis of multi scale entropy with wavelet denoising signal to get multi-scale entropy distribution curve.Then through the analysis of the experimental date with four kinds of fault types of rolling bearing normal condition,inner race fault,ball fault and out race fault,results show that the method of wavelet and multi-scale entropy can effectively distinguish the four types of faults in the scale factor under appropriate,can identify fault of rolling bearing,and is better than the traditional method.更多还原