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提出了一种基于小波包分析的滚动轴承故障诊断方法用于实现滚动轴承早期故障的检测.该方法的诊断过程如下:对轴承原始振动信号进行频谱分析,获取振动信号能量集中的频段.根据频段的范围和振动信号的采样频率确定小波包分解的层数.采用小波包分解的方法提取滚动轴承振动信号中能量集中的频段并生成相应的重构信号,对重构后的振动信号进行Hilbert变换和二次频谱分析.通过对比轴承故障的特征频率和二次频谱中的特征谱线判断轴承是否有故障及其发生位置.运用上述方法对具有外环故障的滚动轴承进行了实验研究并成功地实现了滚动轴承外环故障的检测.实验结果表明基于小波包分析的诊断方法可以有效诊断出滚动轴承的早期故障.
A fault diagnosis method of rolling bearing based on wavelet packet analysis is proposed to detect the early failure of the rolling bearing.The diagnosis process of this method is as follows: Perform spectrum analysis on the original vibration signal of the bearing to obtain the frequency band with concentrated vibration signal energy.According to the scope of the frequency band And the sampling frequency of the vibration signal to determine the number of wavelet packet decomposition.Wavelet packet decomposition method is used to extract the energy concentrated frequency band in the rolling bearing vibration signal and generate the corresponding reconstructed signal.The Hilbert transform and quadratic Spectrum analysis. By comparing the characteristic frequency of the bearing fault and the characteristic spectrum in the secondary spectrum to determine whether the bearing has a fault and its location. The above method is used to study the rolling bearing with outer ring failure and successfully achieve the rolling bearing outer Loop fault detection.The experimental results show that the diagnosis method based on wavelet packet analysis can effectively diagnose the early failure of the rolling bearing.