【作者】 何亮；

【导师】 王奉涛；

【作者基本信息】 大连理工大学 ， 机械电子工程， 2012， 硕士

【摘要】 滚滚动轴承是旋转机械设备中的关键部件,其故障发生率较高,对整个机组能否正常运行有十分重要的影响,所以研究滚动轴承状态监测与故障诊断方法具有重要的意义。本文以滚动轴承为研究对象,深入分析滚动轴承的故障形成原因,总结故障信号的基本特征,应用振动信号处理方法,对滚动轴承故障诊断技术开展了研究工作。论文主要内容如下：1.论述了滚动轴承的基本理论。结合其基本结构和常见故障,指出了表面类损伤类故障信号的特点、给出滚动轴承的故障特征频率计算公式,分析常用的故障诊断方法,并通过实验室采集的故障信号,验证了常用诊断方法的有效性。2.提出了基于EMD-样本熵的早期故障信号降噪方法。滚动轴承早期故障特征信号信噪比较小,这给实际故障诊断带来很多困难,因此本文运用基于EMD滤波处理的降噪方法,提出了基于样本熵值聚类重构的降噪准则,在共振解调问题中引入谱峭度算法。通过工程实际信号验证,基于样本熵准则的EMD滤波处理可以准确地提取滚动轴承早期故障特征。3.提出了基于EMD-ICA的单通道故障信号故障诊断方法。针对滚动轴承故障诊断领域中单通道信号无法应用独立分量分析技术的难题,提出了基于EMD分解的子带ICA方法,利用该方法对单通道信号进行故障特征提取,将信号EMD分解得到的若干IMF分量和源信号共同作为ICA的输入量,实现基于单通道信号的故障诊断。通过仿真和实际信号的诊断结果验证了该方法的有效性。4.利用LabVIEW与MATLAB混合编程技术,开发了滚动轴承故障分析系统。介绍了软件开发环境,设计了系统的总体结构,编程实现了各个模块的功能,通过工程实例验证了该系统的可靠性。更多还原

【Abstract】 Rolling bearing is a key component of the machinery device. It is also the most potential component to fail. It has an important impact to the whole unit whether its working condition is normal, so it is very central to research on bearing condition monitoring and fault diagnosis techniques, in this paper, rolling bearing is the research object. Starting with the failure mechanism and signal characteristics, two new signal processing methods for bearing condition monitoring is studied, and applying signal processing techniques, a series of studies on the fault diagnosis of rolling bearing are carried out. The main works of this dissertation are as follows:1. Rolling bearing basic theory is studied. Based on the analysis of structure, failure mechanism and vibration mechanism of bearing, the function of characteristic and natural frequency of fault bearing is introduced, The common fault diagnosis methods are also studied, and the laboratory acquired signal is used to testify the effectiveness of the common method.2. A denoise method based on EMD-Sample entropy is proposed. The signal to noise ratio is very low in the incipient process because of interfering by normal features and some other noise, and this makes it difficult to actual diagnosis, so how to detect rolling bearing fault in the early stage is very urgent. In the view of the difficulty to solve the problem, EMD denoising based on filter-based processing is used in fault diagnosis, a criterion based on sample entropy is proposed according to the characteristic of faulty signal. Combining spectral kurtosis and EMD denoising theory, it is easy and accurate to detect the fault, Simulated and practical signal are used to verify the effectiveness.3. A bearing fault diagnosis method based on EMD (empirical mode decomposition) and ICA is proposed In the field of applying the ICA to diagnose rolling bearing fault, the single-channel signal is always the big problem, above this, a method of SDICA based on EMD is put forward, the IMFs and original signal are taken as the input of ICA, fault diagnosis is realized accurately by ICA analysis. Simulated and practical signal are used to verify the effectiveness.4.Using LabVIEW and MATLAB hybrid programming, the system of rolling bearing fault diagnosis system is developed, the system development environment and overall structure design are introduced. Then the implement method and function of each module are discussed. Through the analysis and diagnosis of practical vibration signal, the subsystem is verified to be reliable and effective.更多还原