Fault warning method for aircraft engine rolling bearings based on characteristic energy
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摘要:
针对航空发动机滚动轴承实时监测难的问题，提出了基于特征能量的航空发动机滚动轴承故障预警方法。该方法首先对原始振动信号进行CEEMDAN分解得到若干个分量，计算出各个分量的峭度和相关系数；然后依据峭度-相关系数准则筛选出强冲击分量重构并进行包络解调，最大程度地保留与轴承故障冲击性成分相关的有效信息；最后由包络谱中的信息计算故障轴承与正常轴承的特征能量，由此建立诊断基线与特征能量带，实现对轴承运行状态的监测。利用凯斯西储大学深沟球轴承试验台数据、搭建的滚动轴承试验台数据和涡扇航空发动机轴承部件试验器条件下的数据对该方法的有效性进行验证。结果表明计算得到外圈故障轴承特征能量占整个包络谱能量的比例为59.5%～75.9%，该方法可为航空发动机主轴承故障诊断及在线监测提供有效手段。
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关键词:
- 滚动轴承 /
- 故障诊断 /
- 峭度-相关系数筛选准则 /
- 特征能量 /
- 故障预警
Abstract:A method for real-time monitoring of rolling bearings in aircraft engines based on characteristic energy was proposed to address the challenging issue of real-time monitoring of rolling bearings in aircraft engines. This method first decomposed the original vibration signal using CEEMDAN to obtain several components, and then calculated the kurtosis and correlation coefficient of each component. Subsequently, based on the kurtosis-correlation coefficient criterion, it selected strong impact components for reconstruction and performed envelope demodulation to maximally retain effective information related to bearing fault impact components. Finally, the method calculated the characteristic energy of faulty and normal bearings from the information in the envelope spectrum, established a diagnostic baseline and characteristic energy belt, and achieved monitoring of bearing operating status. The effectiveness of this approach was validated using data from the Case Western Reserve University deep groove ball bearing test rig, a constructed rolling bearing test rig, and a test rig for a certain type of turbofan aircraft engine bearing component. The results showed that the proportion of the characteristic energy of the outer ring fault bearing in the whole envelope spectrum energy was 59.5%—75.9%, and the method can provide an effective means for the fault diagnosis and online monitoring of the main bearing of aircraft engine.
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图 3 诊断基线及特征能量带示意图
Figure 3. Diagnostic baseline and characteristic energy belt diagram
图 7 内圈故障仿真信号重构的包络谱
Figure 7. Envelope spectrum of inner loop fault simulation signal reconstruction
图 8 内圈故障仿真信号重构的局部包络谱
Figure 8. Local envelope spectrum of inner loop fault simulation signal reconstruction
图 11 CWRU故障轴承外圈信号CEEMDAN分解后各分量筛选指数
Figure 11. Screening index of each component of CWRU fault bearing signal after CEEMDAN decomposition
图 12 CWRU故障轴承外圈故障重构信号包络谱
Figure 12. CWRU bearing outer ring fault reconstruction signal envelope spectrum
图 13 CWRU轴承外圈故障重构信号包络谱局部0～250 Hz
Figure 13. CWRU bearing outer ring fault reconstruction signal envelope spectrum local 0—250 Hz
图 15 CWRU正常轴承故障特征能量占比
Figure 15. CWRU normal bearing fault characteristic energy ratio
图 16 CWRU滚动轴承外圈故障诊断基线及特征能量带
Figure 16. Fault diagnosis baseline and characteristic energy belt of CWRU rolling bearing outer ring
图 17 加入6 dB高斯白噪声后的时域信号
Figure 17. Time domain signal after adding 6 dB white Gaussian noise
图 19 加入强背景噪声后的特征能量占比
Figure 19. Characteristic energy ratio after adding strong background noise
图 20 不同测点的故障特征能量占比
Figure 20. Fault characteristic energy ratio of different measuring points
图 22 CWRU轴承内圈故障重构信号包络谱
Figure 22. CWRU bearing inner ring fault reconstruction signal envelope spectrum
图 23 CWRU轴承内圈故障重构信号包络谱局部0～300 Hz
Figure 23. CWRU bearing inner ring fault reconstruction signal envelope spectrum local 0—300 Hz
图 24 CWRU滚动轴承内圈故障诊断基线及特征能量带
Figure 24. Fault diagnosis baseline and characteristic energy belt of CWRU rolling bearing iner ring
图 27 轴承外圈故障重构信号包络谱
Figure 27. Bearing outer ring fault reconstruction signal envelope spectrum
图 28 轴承外圈故障重构信号包络谱局部0～150 Hz
Figure 28. Bearing outer ring fault reconstruction signal envelope spectrum local 0—150 Hz
图 31 轴承外圈故障诊断基线及特征能量带
Figure 31. Fault diagnosis baseline and characteristic energy belt of bearing outer ring
图 32 航空发动机主轴承剥落故障试验台
Figure 32. Test bench for main bearing spalling failure of a certain type of aircraft engine
图 34 部件试验器主轴承振动采集系统示意图
Figure 34. Schematic diagram of vibration acquisition system for main bearing of component tester
图 36 CEEMDAN分解后各分量筛选指数
Figure 36. Screening index of each component after CEEMDAN decomposition
图 37 轴承外圈故障重构信号包络谱
Figure 37. Bearing outer ring fault reconstruction signal envelope spectrum
图 38 滚动轴承外圈故障诊断基线及特征能量带
Figure 38. Fault diagnosis baseline and characteristic energy belt of bearing outer ring
表 1 应用的深沟球轴承参数
Table 1. Application of deep groove ball bearing parameters
滚动体节径
Dr/mm滚动体直径
dr/mm接触角
α/（°）滚动体个数
Z/个39.04 7.94 0 9 
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表 2 CWRU故障轴承和正常轴承特征能量占比
Table 2. Characteristic energy ratio of CWRU faulty bearing and normal bearing
转速/
（r/min）特征能量占比/% 外圈故障 内圈故障 滚动体故障 正常轴承 1730 59.5 7.9 9.6 3.5 1750 79.1 10.2 1.4 2.3 1772 61.0 12.8 8.2 2.2 1797 62.7 9.9 6.8 1.4
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表 3 加入噪声后故障轴承和正常轴承特征能量占比
Table 3. Characteristic energy ratio of faulty bearing and normal bearing after adding noise
加入噪声/dB 能量占比/% 故障轴承 正常轴承 2 15.2 5.9 4 14.5 5.6 6 11.0 5.4 8 10.7 4.7
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表 4 不同转速下故障轴承和正常轴承的故障特征能量百分比
Table 4. Fault characteristic energy ratio of faulty bearing and normal bearing at different speeds
转速/
（r/min）能量占比 3点故障位置 6点故障位置 12点故障位置 正常轴承 1730 27.9 59.5 27.2 3.5 1750 49.5 79.1 32.8 2.3 1772 28.0 61.0 24.2 2.2 1797 33.7 62.7 23.4 1.4
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表 5 CWRU故障轴承和正常轴承特征能量百分比
Table 5. Characteristic energy ratio of CWRU faulty bearing and normal bearing inner rings
转速/
（r/min）能量占比/% 内圈故障 外圈故障 滚动体故障 正常轴承 1730 63.6 11.8 16.7 3.7 1750 50.3 1.27 5.8 2.7 1772 43.5 1.5 4.0 2.6 1797 54.9 1.5 7.4 1.0
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表 6 试验轴承参数
Table 6. Experimental bearing parameters
滚动体节径
Dr/mm滚动体直径
dr/mm接触角
α/（°）滚动体个数
Z/个33.5 7 0 11
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表 7 典型故障轴承和典型正常轴承特征能量百分比
Table 7. Characteristic energy percentage of classic faulty bearing and classic normal bearing
转速/
（r/min）能量占比/% 外圈故障 内圈故障 滚动体故障 正常轴承 740 75.3 16.2 19.3 13.5 840 71.7 4.8 7.6 12.2 960 64.2 9.9 16.1 10.6 1080 56.7 14.8 10.7 13.4 1200 65.8 16.8 23.2 11.4 1320 62.7 16.3 25.4 8.8 1440 54.5 7.2 19.5 9.2 1560 65.4 4.5 12.1 10.6
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表 8 故障轴承和正常轴承特征能量占比
Table 8. Characteristic energy ratio of faulty bearing and normal bearing
转速/
（r/min）能量占比/% 外圈故障 正常轴承 10443 25.6 8.2 13208 28.5 7.8 14340 23.6 5.6 14675 29.5 7.6
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