Matlab重载货运列车滚动轴承振动故障分析
这次毕业设计的目的是利用谐波小波与近似熵两种方法对含噪声的振动信号进行分析，有噪声和无噪声振动的区别，以此来判断滚动轴承是否有故障。
设计中运用了小波和近似熵相结合的方法。近似熵是一个从衡量时间序列复杂性的角度出发的反映信号整体特征的指标,其具有计算所需数据短,对确定性信号和随机信号都有效的特点。近似熵对复杂的信号有很强的的处理能力。8064
现有的方法对于非平稳性的信号的处理和分析不是很完善，所以我在接下来的解决方案中运用了小波的方法。对主要的谐波小波和复morlet概念和性质进行叙述。从小波的频谱出发运，在简单的解析表达式的谐波小波的运用，并经过严格的数学推导，得到了基于FFT的谐波小波算法，最后通过引用实际实例和相关编程实验表明,以复morlet小波在提取故障信号的特征方面同样具有很强的能力。关键词：信号处理，近似熵，小波变换,小波包。
Analysis of rolling bearing vibration faults of heavy-haul freight train
Abstract：Rolling bearing is one of the important components of the train operation, its health status directly affects the safe operation of the train, so for the safety inspection of rolling bearing is the key.
The purpose of the thesis is the harmonic wavelet and the analysis of vibration signal containing noise using approximate entropy difference between the two methods, with and without noise vibration, in order to determine whether the fault of rolling bearing.
Design by using the method of combination of wavelet and approximate entropy. Approximate entropy is the overall characteristics of a measure of time series complexity from the angle of the reflected signal index, which has the characteristics of short, effective for deterministic and random signals. Approximate entropy has strong processing ability for complex signal.
The existing methods for the processing and analysis of nonstationarity is not very perfect, so I used the wavelet method in the solution of the next. Narrating the harmonic wavelet major and complex Morlet concepts and properties. Shipped out from the wavelet spectrum, using the simple analytical expressions for the harmonic wavelet, and through strict mathematical derivation, harmonic wavelet algorithm based on FFT is obtained, finally by reference to the actual examples and related programming experiment showed that, using complex Morlet wavelet in the feature extraction of fault signal also has a strong ability to.
Key words：Signal processing, approximate entropy, wavelet transform，Wavelet packet
目录
1 绪论 1
1.1 本课题的意义、目的和发展趋势 1
1.1.1 课题意义和目的 1
1.1.2 发展趋势 1
1.2 主要工作安排 2
2 列车滚动轴承故障诊断基础原理 3
2.1 列车滚动轴承振动原理 3
2.2 滚动轴承固有频率、特征频率及频谱结构 5
2.2.1 固有频率 5
2.2.2 特征频率 5
2.2.3 频谱结构 7
2.3 列车滚动轴承振动信号的检测 8
3 小波变换的介绍基本原理及应用 8
3.1 简要介绍 8
3.2 小波变换对于信号降噪的原理 9
3.2.1 小波分析用于信号处理的过程 9
3.2.2 小波变换降噪基本模型 9
3.3 小波包的分析 10