利用混沌吸引子阶跃变化现象检测滚动轴承微弱故障

Weak fault detection of rolling bearing based on step change of chaotic attractor

针对现有的基于混沌振子的微弱信号检测方法存在混沌状态判据计算复杂、混沌状态临界点难以精确确定的问题,提出一种基于混沌吸引子形状阶跃变化的微弱信号检测方法。通过分析典型的混沌系统的动力学特性,将吸引子出现阶跃变化作为存在待测频率信号的判断依据,提出自适应选取阈值和自动判断混沌吸引子变化的方法,在此基础上,设计基于混沌吸引子形状阶跃变化的微弱信号检测系统。最终将该系统应用于滚动轴承的早期微弱故障诊断中。研究结果表明:该方法为基于混沌振子的微弱信号检测提供了一种具有新定量判断准则的方法,不仅能够实现自动检测微弱信号频率,提高基于混沌振子的微弱信号检测方法的检测性能,而且在滚动轴承的微弱故障信号检测中易于实现,具有实际应用价值。

There are some problems in the existing chaotic state criterion,such as the calculation of qualitative chaotic state criterion is complicated,the critical point of quantitative chaotic state criterion is difficult to be determined,and the threshold value is not accurate enough.In order to solve these problems,a new method of weak signal detection based on chaotic attractor shape step change was proposed.Based on the analysis of the dynamic characteristics of several typical chaotic systems,the special properties of one attractor in the step change from one attractor to another attractor were taken as the basis of whether the frequency components to be measured were kept or not,and then the weak signal detection was realized.Finally,the proposed scheme was applied to the early weak fault diagnosis of rolling bearings.The results show that the method not only provides an effective quantitative judgment criterion,but also realizes the automatic selection of threshold and the automatic judgment of chaotic state.This new method has a better performance in weak signal detection,which can serve an effective method for weak fault signal detection of machinery.