基于混沌分形理论的滚动轴承微小故障诊断

发布时间：2019-05-28 21:15

【摘要】：为提取轴承微小故障的故障特征,提出一种基于混沌分形理论的滚动轴承故障诊断方法。通过计算滚动轴承振动信号的最大Lyapunov指数,进行轴承运动的混沌识别;然后,对具有混沌特性的振动信号,计算关联维数和盒维数作为故障诊断的状态特征量。当关联维数不能明显区别轴承故障时,利用关联维数与盒维数相结合的方法判别故障;最后,选取滚动轴承滚动体、内圈、外圈存在微小故障和较明显故障以及正常状态7种工况的振动信号进行实验。研究结果表明:该方法能准确提取故障特征并完成滚动轴承的微小故障诊断。该方法为滚动轴承故障诊断提供了新的有效途径。
[Abstract]:In order to extract the fault characteristics of bearing minor faults, a rolling bearing fault diagnosis method based on chaotic fractal theory is proposed. The chaotic identification of bearing motion is carried out by calculating the maximum Lyapunov index of rolling bearing vibration signal. Then, for the vibration signal with chaotic characteristics, the correlation dimension and box dimension are calculated as the state characteristics of fault diagnosis. When the correlation dimension can not distinguish the bearing fault obviously, the method of combining the correlation dimension with the box dimension is used to distinguish the fault. Finally, the vibration signals of rolling bearing rolling body, inner ring and outer ring with small and obvious faults and normal state are selected to carry out the experiment. The results show that this method can accurately extract the fault features and complete the micro fault diagnosis of rolling bearings. This method provides a new and effective way for fault diagnosis of rolling bearings.
【作者单位】：昆明理工大学信息工程与自动化学院;云南省矿物管道输送工程技术研究中心;
【基金】：国家自然科学基金资助项目(51169007) 云南省科技计划项目(2013DH034,2012CA022,2011CI017)~~
【分类号】：TH133.3;O415.5

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