【作者】 张博；

【导师】 王凯；

【作者基本信息】 西安理工大学 ， 机械电子工程， 2009， 硕士

【摘要】 滚动轴承是大部分旋转机械的基本组成部件,也是易损零件,许多旋转机械中的故障都与滚动轴承有关。因此,研究滚动轴承的故障诊断方法具有十分重要的意义。本文以提取滚动轴承振动信号的特征及其故障诊断为主线,在分析了传统滚动轴承的振动信号处理方法的基础上,以Hilbert-Huang变换的时频分析方法为重点,对滚动轴承故障特征提取和故障诊断方法进行探索和研究,并对滚动轴承典型故障的振动信号进行分析和验证。最后,在此基础上开发出滚动轴承振动信号分析软件。论文首先研究了滚动轴承的常见失效形式及其特征,并对滚动轴承的振动机理和振动信号进行了深入研究。针对几种常用的滚动轴承故障特征提取的时频分析方法：短时傅里叶变换、Wigner-Ville分布、小波变换等进行了研究。对Hilbert-Huang算法中涉及的采样数据延拓技术开展了研究,以减弱端点效应；利用中值滤波技术来克服模态裂解问题；通过仿真比较,发现Rilling的IMF筛选终止准则具有较好的数据处理特性。论文利用多种时频分析方法对仿真信号进行特征提取,再把基于Hilbert-Huang的时频分析方法与典型的时频分析方法进行对比研究,指出该方法对于分析非平稳信号具有更好的有效性和优越性。论文利用基于Hilbert-Huang的时频分析方法对实测的滚动轴承故障振动信号进行了分析。实验研究表明,Hilbert-Huang方法对滚动轴承故障诊断具有很好的有效性和可行性。最后,本文开发出交互式用户界面,便于分析程序的实际应用。论文的研究内容为滚动轴承故障特征提取及分析提供了新的思路。更多还原

【Abstract】 The rolling bearing is basic component part of the most rotating machinery, and it is damaged easily. On account of this, many faults of rotating machinery have great relationship with it. Therefore, it is of importance to study fault diagnosis methods. In this paper, main attention has been put on extracting the feature of vibration signal and investigation on fault diagnosis for rolling bearing. Based on the analysis of the traditional processing methods of vibration signal, focusing on the time-frequency analysis method based on Hilbert-Huang transform, the feature extraction and fault diagnosis methods for rolling bearing have been investigated. And analysis and validation for the vibration signal of typical fault for roller bearing have been done. Finally the vibration signal analysis software for rolling bearing was developed.First of all, the common failure mode and characteristics of rolling bearing were analyzed in this paper, the vibration mechanism and characteristics of rolling bearing were deeply studied. Several commonly used time-frequency analysis methods have been researched too, such as Short-time Fourier transform, Wigner-Ville distribution and Wavelet transform.The extending technology of sampled data related in Hilbert-Huang algorithm were studied to diminish the end effects; The median filtering was used to overcome the problem of mode decomposition; According simulation and comparison, it was found that the Rilling termination criteria for the sifting of the IMF has better properties in data-processing.Features of simulated signal were extracted through a variety of time-frequency analysis methods, compared with the typical time-frequency analysis methods, we find Hilbert-Huang transform has more validity and superiority in fields of analyzing non-stationary signal.The actual fault vibration signals of rolling bearing were analiyed with the time-frequency method based on Hilbert-Huang. It has been showed that Hilbert-Huang method was more effective and feasible. Finally, an interactive user interface was developed in this paper, which is used for practical application of analyzing programs.This paper provides a new way for fault feature extraction and analysis for rolling bearing.更多还原