小波分析及在轴承故障诊断中的应用【毕业论文】.doc
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本科毕业设计
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小波分析及在轴承故障诊断中的应用
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专业班级 电气工程及其自动化
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摘 要
【摘要】本文研究的内容是小波分析在轴承故障诊断中的应用。主要是利用小波分析中的尺度分析方法,因小波分析具有良好的时-频定位特性及对信号的自适应能力,故而能对各种时变信号进行分解。小波变换中具有多分辨率分析的特点,因此具有对非平稳信号局部化分析的优点,适合探测正常信号中夹带的瞬态反常现象并展示其成分。对于表面损伤类故障我们可以看到损伤点滚过轴承元件表面会出现冲击力(脉冲力),产生的信号很宽往往就会掩盖住轴承系统的固有的频率使得轴承的产生振动。这种因为表面损伤故障引起的振动响有时会被较大的振动信号覆盖了,使得我们在功率谱中无法分辨出来。故所以要用小波分析信号的时域和频域这种特性,然后故障进行数学计算算出外,内环及滚动体的故障频率。接着对信号进行变换和重构,最后通过希尔波特变换进行解调和细化频谱分析,这样我们就可以从轴承中检测出故障信号,再判断轴承发生故障的部位。最后一步计划是设计GUI界面,通过GUI的工具对波形信号进行进一步细化的仿真分析。
【关键词】尺度分析方法;小波变化;时域;频域。
Abstract
【ABSTRACT】 The contents of this paper is to wavelet analysis in bearing fault diagnosis. Mainly in the scale of wavelet analysis method, because wavelet analysis has good time - frequency localization properties and adaptive capacity of the signal, therefore a variety of time-varying signals can be decomposed. Wavelet analysis has the characteristics of multi-resolution, so it has to non-stationary signal analysis of the advantages of localization, the normal signal for detecting anomalies of transient entrainment and show its composition. For the class of surface damage point of failure we can see the damage there will be rolled over the bearing element surface impact (pulse power), the resulting signal will tend to conceal the very wide bearing system natural frequency of vibration makes the bearings. Such as surface damage caused by the vibration of ring faults are sometimes covered a large vibration signal, making the power spectrum we can not tell the difference. So why use of wavelet analysis and time domain frequency domain this feature, then failure to work out mathematical calculations, the inner ring and rolling element fault frequency. Then, the signal transformation and reconstruction, and finally demodulated by Hilbert transform and refine the spectrum, so that we can detect from the bearing fau
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