Rolling bearing quality evaluation based on a morphological filter and a Kolmogorov complexity measure

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• 作者：Kuosheng Jiang (1)
  Guanghua Xu (1) (2)
  Tangfei Tao (1) (3)
  Lin Liang (1) (2)
  
  1. School of Mechanical Engineering ; Xi鈥檃n Jiaotong University ; Xi鈥檃n ; 710049 ; China
  2. State Key Laboratory for Manufacturing System Engineering ; Xi鈥檃n Jiaotong University ; Xi鈥檃n ; 710049 ; China
  3. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System ; Xi鈥檃n ; 710049 ; China
  
• 关键词：Eddy current sensor ; Kolmogorov complexity ; Morphology filter ; Bearing quality control
• 刊名：International Journal of Precision Engineering and Manufacturing
• 出版年：2015
• 出版时间：March 2015
• 年：2015
• 卷：16
• 期：3
• 页码：459-464
• 全文大小：1,012 KB
• 参考文献：1. Rafsanjani, A., Abbasion, S., Farshidianfar, A., Moeenfard, H. (2009) Nonlinear Dynamic Modeling of Surface Defects in Rolling Element Bearing Systems. Journal of Sound and Vibration 319: pp. 1150-1174 CrossRef
  2. Law, L. S., Kim, J., Liew, W., Lee, S. K. (2013) An Approach to Monitoring the Thermomechanical Behavior of a Spindle Bearing System using Acoustic Emission (AE) Energy. Int. J. Precis. Eng. Manuf. 14: pp. 1169-1175 CrossRef
  3. Jian, H., Lee, H. R., Ahn, J. H. (2013) Detection of Bearing/Rail Defects for Linear Motion Stage using Acoustic Emission. Int. J. Precis. Eng. Manuf. 14: pp. 2043-2046 CrossRef
  4. Biswas, P. V., Ahn, J. H., Lee, H. R. (2013) Monitoring of Bearing Wear in a Marine Engine by Change of Piston Position-Effect of Wear and Inertia. Int. J. Precis. Eng. Manuf. 14: pp. 1697-1701 CrossRef
  5. Chen, Y., He, Z., Yang, S. (2012) Research on On-Line Automatic Diagnostic Technology for Scratch Defect of Rolling Element Bearings. Int. J. Precis. Eng. Manuf. 13: pp. 357-362 CrossRef
  6. Lu, S., He, Q., Kong, F. (2014) Stochastic Resonance with Woods-Saxon Potential for Rolling Element Bearing Fault Diagnosis. Mechanical Systems and Signal Processing 45: pp. 488-503 CrossRef
  7. Ming, Y., Chen, J., Dong, G. (2011) Weak Fault Feature Extraction of Rolling Bearing based on Cyclic Wiener Filter and Envelope Spectrum. Mechanical Systems and Signal Processing 25: pp. 1773-1785 CrossRef
  8. Lei, Y., Lin, J., He, Z., Zi, Y. (2011) Application of an Improved Kurtogram Method for Fault Diagnosis of Rolling Element Bearings. Mechanical Systems and Signal Processing 25: pp. 1738-1749 CrossRef
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  13. Hong, H., Liang, M. (2009) Fault Severity Assessment for Rolling Element Bearings using the Lempel-Ziv Complexity and Continuous Wavelet Transform. Journal of Sound and Vibration 320: pp. 452-468 CrossRef
  14. Wang, J., Xu, G., Zhang, Q., Liang, L. (2009) Application of Improved Morphological Filter to the Extraction of Impulsive Attenuation Signals. Mechanical Systems and Signal Processing 23: pp. 236-245 CrossRef
  15. Maragos, P., Schafer, R. W. (1987) Morphological Filters-Part I: Their Set-Theoretic Analysis and Relations to Linear Shift-Invariant Filters. IEEE Transactions on Acoustics, Speech and Signal Processing 35: pp. 1153-1169 CrossRef
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• 刊物类别：Engineering
• 刊物主题：Industrial and Production Engineering
  Materials Science
  
• 出版者：Korean Society for Precision Engineering, in co-publication with Springer Verlag GmbH
• ISSN：2005-4602

文摘

Bearing defective inspection plays a vital role in bearing quality control. Unlike signals in the process of condition monitoring and fault diagnosis, the signal characteristic of defective bearings is much weaker and difficult to be quantified through the acceleration based techniques. In this paper, a novel system is developed to inspect automatically the small defects of roller bearings for on-line quality control. Rather than using acceleration based techniques the system employs a high sensitive eddy current sensor to measure the displacement profiles of the outer race for high signal to noise ratio. Furthermore, a morphological filter is used to enhance the feature signal which is subsequently measured by Kolmogorov complexity measure. Both simulated signals and measured data show that this system is able to diagnose defects including abnormal surface roundness, waviness, misaligned races which are typical quality problems in bearing manufacturing lines.