Rolling bearing fault diagnosis method based on wavelet packet transform and CEEMDAN
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摘要:
针对滚动轴承诊断受环境噪声影响，特征频率难以提取的问题，提出了一种基于小波包变换与完全自适应噪声集合经验模态分解（CEEMDAN）的滚动轴承故障诊断方法。通过CEEMDAN将传感器收集到的原始振动信号进行分解并依据峭度值-相关系数（K-C）筛选准则划分高噪信号和低噪信号。利用小波包变换分解高噪信号后选取合适分量重构实现环境噪声的滤除并与低噪信号进行整合产生新的振动信号进行包络解调，提取实际故障特征频率实现滚动轴承的故障诊断。经对比试验，所提出的方法清晰地提取出滚动轴承的转频、故障特征频率及其倍频和调制频率，由仿真信号计算可知降噪后的信号信噪比提高了7.61 dB，有效优化了对噪声滤除的效果。
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关键词:
- 完全自适应噪声集合经验模态分解（CEEMDAN） /
- 峭度值-相关系数筛选准则 /
- 小波包变换 /
- 包络解调 /
- 特征频率 /
- 故障诊断
Abstract:For the problem that rolling bearing diagnosis is affected by the environmental noise so that extraction of characteristic frequency is difficult, a rolling bearing fault diagnosis method based on wavelet packet transform and complete ensemble empirical model decomposition adaptive noise (CEEMDAN) was proposed. The raw vibration signal collected by the sensor was split through CEEMDAN and the high-noise signal and low-noise signal were divided through the kurtosis-correlation coefficient screening criteria (K-C). The wavelet packet transform was used to split the high noise signal and then select appropriate component reconstruction to filter out the environmental noise and integrate with the low noise signal to generate a new vibration signal for envelope demodulation, and the actual fault characteristic frequency was extracted to achieve fault diagnosis of rolling bearings. After comparative experiments, the method proposed clearly extracted the rotational frequency, fault characteristic frequency and its frequency multiplier and modulation frequency of rolling bearings, and the signal-noise ratio after noise reduction was increased by 7.61 dB from the simulation signal calculation, which effectively optimized the effect of noise filtering.
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图 4 去噪后的重构信号0～0.2 s时域图
Figure 4. Reconstructed signal 0−0.2 s time domain diagram after denoising
图 5 外圈故障仿真信号重构信号0～1000 Hz频率范围的包络谱
Figure 5. Envelope spectrum of the reconstructed simulation signal in the 0−1000 Hz frequency range of the outer ring fault
图 6 西储大学简单路径故障轴承模拟试验台
Figure 6. Western Reserve University simple path fault bearing simulation test bench
图 7 简单路径内圈故障样本原始信号时域图
Figure 7. Inner ring fault sample raw signal time domain diagram of simple path
图 8 重构信号0～800 Hz频段频谱
Figure 8. Spectrum of the reconstructed signal in the 0−800 Hz band
图 9 简单路径内圈故障样本重构信号时域图像
Figure 9. Reconstructed signal time domain diagram of inner ring fault sample of simple path
图 10 简单路径内圈故障样本重构信号包络谱
Figure 10. Envelope spectrum of the inner ring fault sample reconstructed signal of simple path
图 11 简单路径外圈故障样本原始信号时域图
Figure 11. Outer ring fault sample raw signal time domain diagram of simple path
图 12 简单路径外圈故障样本重构信号时域图像
Figure 12. Reconstructed signal time domain diagram of outer ring fault sample of simple path
图 13 简单路径外圈故障样本重构信号包络谱
Figure 13. Envelope spectrum of the outer ring fault sample reconstructed signal of simple path
图 14 中介轴承故障模拟试验台系统
Figure 14. Intermediate bearing simulation test bench overall system
图 16 中介轴承故障模拟试验台结构及故障信号传递路径示意图
Figure 16. Intermediate bearing simulation test bench interaxial structure and fault signal transmission path
图 20 复杂路径外圈样本原始信号与去噪信号对比
Figure 20. Outer ring sample raw signal versus denoising signal of complex path
图 21 复杂路径外圈故障样本重构信号局部包络谱
Figure 21. Envelope spectrum of the outer ring fault sample reconstructed local signal of complex path
图 22 复杂路径内圈样本原始信号与去噪信号对比
Figure 22. Inner ring sample raw signal versus denoising signal of complex path
图 23 复杂路径内圈故障重构信号局部包络谱
Figure 23. Envelope spectrum of the inner ring fault sample reconstructed local signal of complex path
图 24 复杂路径内圈故障小波包变换故障诊断结果
Figure 24. Inner ring fault wavelet packet transformation fault diagnosis results of complex path
表 1 峭度值-相关系数筛选准则信号划分标准
Table 1. Steepness values-correlation coefficient screening criteria signal division criteria
对比结果 信号划分 W ≥ C 高噪信号 W < C 低噪信号 
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表 2 6205-2RS JEM SKF深沟球轴承参数
Table 2. Parameters of 6205-2RS JEM SKF deep groove ball bearings
参数 数值 轴承滚道节径/mm 39.0390 滚珠直径/mm 7.940 接触角/（°） 0 滚珠数 9
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表 3 内、外圈故障试验样本参数
Table 3. Inner and outer ring fault parameters of experiments sample
参数 数值 转速/（r/min） 1797 故障直径/mm 0.1778 故障深度/mm 0.2794 电动机功率/W 0
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表 4 简单路径内圈原始信号对比参数
Table 4. Inner ring raw signal comparison parameters of simple path
K0 T C 5.3959 0.2149 1.2149
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表 5 简单路径内圈高噪信号分量参数
Table 5. High noise signal component parameters of the inner ring of a simple path
序号 Kc rc W 1 1.5715 0.4162 1.9877 2 0.8055 0.8349 1.6404 3 1.1463 0.3623 1.5085
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表 6 简单路径外圈原始信号对比参数
Table 6. Outer ring raw signal comparison parameters of simple path
K0 T C 7.6494 0.2286 1.2286
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表 7 简单路径外圈高噪信号分量参数
Table 7. High noise signal component parameters of the outer ring of a simple path
序号 Kc rc W 1 0.7807 0.9739 1.7546 2 1.4033 0.3271 1.7304 3 1.1699 0.0626 1.2325
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表 8 试验轴承结构参数
Table 8. Experimental bearing structural parameters
参数 数值 Z 34 Ro/mm 140 Ri/mm 110 d/mm 8 $ \alpha $/（°） 0
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表 9 加速度传感器参数
Table 9. Acceleration sensor parameters
测点 序列号 灵敏度/（mV/（m/s2） ） as/g ar/g 1 28389 10.04 ±50 0.000 15 2 28390 10.05 3 28391 9.84 4 28392 10.00
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