基于EMD重采样和粗糙集的变转速滚动轴承故障诊断方法研究

发布时间：2018-03-12 13:30

本文选题：故障诊断　切入点：变转速滚动轴承　出处：《北京交通大学》2012年硕士论文　论文类型：学位论文

【摘要】：现在,机械设备工作环境变化多样,机械状态的变化导致振动信号存在有大量的非平稳信号。长久以来,大部分机械故障诊断都是根据平稳工况下所体现的信息情况来分析的。然而,随着故障诊断的快速发展和现实要求的不断提高,如何对非平稳信号进行有效分析成为故障诊断领域的一个关键问题。本文采用了EMD重采样方法对变转速滚动轴承振动信号的EMD分解结果进行了平稳化处理,有效的消减了转速变化对信号频域分析的影响,并根据粗糙集方法分析重采样信号特征,判别故障,取得了良好的效果。首先,分析、实现并验证了EMD分解和EMD重采样方法,利用该方法对变频模拟信号的分析结果表明重采样方法可以令IMF频域特征更加明显,说明该方法对分析变转速信号是有效的。其次,根据特征参数分析方法,计算了传统时域、频域特征参数对EMD重采样结果特征敏感性,筛选了用以表征状态特征的特征参数与IMF,得到了表征信号特征明显的特征参数。最后,将所得的信号特征值作为其条件属性,根据粗糙集方法对特征属性进行了属性值约简,得出了用于诊断故障的决策表。设计了变转速滚动轴承故障诊断方法流程,并通过实验证明该方法有效,诊断准确度比较高。
[Abstract]:Now, a variety of mechanical equipment working environment, changes in mechanical condition lead to vibration signal has a large number of non-stationary signal. For a long time, most of the machinery fault diagnosis are information based on the stationary condition of analysis. However, with the rapid development of fault diagnosis and the practical requirements continue to increase, how to effectively the analysis of non-stationary signals is becoming a key issue in the field of fault diagnosis.
This paper uses the variable speed of rolling bearing vibration signal EMD decomposition results of the stationary processing EMD resampling method, effectively reduce the impact analysis of the speed change of signal frequency, and the fault analysis method based on rough set resampling signals, and achieved good results.
First, we analyze, implement and verify the EMD decomposition and EMD resampling method. Using the method to analyze the frequency conversion analog signal, it is shown that the resampling method can make the IMF frequency domain characteristics more obvious, which shows that this method is effective for analyzing the variable speed signal.
Secondly, according to the characteristic parameter analysis method, we calculated the sensitivity of the traditional time domain and frequency domain characteristic parameters to the EMD resampling results, and screened the characteristic parameters and IMF used to characterize the state characteristics, and got the characteristic parameters that characterize the signal characteristics.
Finally, the signal characteristics of the value as its condition attributes, based on rough set method of feature attributes by attribute value reduction, decision table for fault diagnosis is obtained. The design process of variable speed rolling bearing fault diagnosis method, and the experimental results proved that the method is effective, the diagnostic accuracy is relatively high.

【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH133.331;TH165.3

【参考文献】