Signal processing techniques for rolling element bearing spall size estimation
•The empirical model of the entry event improves the precision to identify the entry point from the bearing vibration signal to improve estimation result.•The VMD is used to remove high frequency noises from the entry signal to help identify the entry point.•Signal processing techniques developed in...
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| Published in | Mechanical systems and signal processing Vol. 117; pp. 16 - 32 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
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15.02.2019
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| Abstract | •The empirical model of the entry event improves the precision to identify the entry point from the bearing vibration signal to improve estimation result.•The VMD is used to remove high frequency noises from the entry signal to help identify the entry point.•Signal processing techniques developed in this paper are easier to be implemented in an automatic diagnostic system.
This paper proposes signal processing techniques to extract entry and exit points from the bearing vibration signal for spall size estimation. The entry point is the start point of a low frequency response when a rolling element enters a localized defect on the raceway, which is contaminated with background noises and difficult to identify. An empirical model based signal processing method is proposed to effectively identify the entry point. The Variational Mode Decomposition (VMD) is applied to the bearing entry signal for more accurate estimation. Differentiation technique is used to identify the high frequency exit point with more reliable threshold values for automatic diagnostics. Then, based on defect size estimation models for both inner and outer race defects, the spall size can be estimated. The proposed methodology is validated on a machine tool spindle’s bearing system. Experimental results show that the proposed signal processing techniques provide less biased results with respect to spindle speed and more precise estimation. |
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| AbstractList | •The empirical model of the entry event improves the precision to identify the entry point from the bearing vibration signal to improve estimation result.•The VMD is used to remove high frequency noises from the entry signal to help identify the entry point.•Signal processing techniques developed in this paper are easier to be implemented in an automatic diagnostic system.
This paper proposes signal processing techniques to extract entry and exit points from the bearing vibration signal for spall size estimation. The entry point is the start point of a low frequency response when a rolling element enters a localized defect on the raceway, which is contaminated with background noises and difficult to identify. An empirical model based signal processing method is proposed to effectively identify the entry point. The Variational Mode Decomposition (VMD) is applied to the bearing entry signal for more accurate estimation. Differentiation technique is used to identify the high frequency exit point with more reliable threshold values for automatic diagnostics. Then, based on defect size estimation models for both inner and outer race defects, the spall size can be estimated. The proposed methodology is validated on a machine tool spindle’s bearing system. Experimental results show that the proposed signal processing techniques provide less biased results with respect to spindle speed and more precise estimation. This paper proposes signal processing techniques to extract entry and exit points from the bearing vibration signal for spall size estimation. The entry point is the start point of a low frequency response when a rolling element enters a localized defect on the raceway, which is contaminated with background noises and difficult to identify. An empirical model based signal processing method is proposed to effectively identify the entry point. The Variational Mode Decomposition (VMD) is applied to the bearing entry signal for more accurate estimation. Differentiation technique is used to identify the high frequency exit point with more reliable threshold values for automatic diagnostics. Then, based on defect size estimation models for both inner and outer race defects, the spall size can be estimated. The proposed methodology is validated on a machine tool spindle’s bearing system. Experimental results show that the proposed signal processing techniques provide less biased results with respect to spindle speed and more precise estimation. |
| Author | Kurfess, Thomas R. Chen, Aoyu |
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| Cites_doi | 10.1016/j.protcy.2014.08.003 10.1115/1.4027334 10.1109/TSP.2013.2288675 10.1016/j.ymssp.2014.06.006 10.1016/j.chaos.2004.12.014 10.1115/1.4003595 10.1016/j.jsv.2017.03.007 10.1016/j.ymssp.2007.12.001 10.1016/j.measurement.2017.09.018 10.1016/j.ymssp.2014.04.014 10.1016/j.ymssp.2010.09.009 10.1007/978-3-319-06590-8_48 10.1016/j.jsv.2015.12.011 10.1016/j.jsv.2016.09.014 |
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| Keywords | Variational Mode Decomposition (VMD) Spall size estimation Rolling element bearing |
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Sound Vib. doi: 10.1016/j.jsv.2015.12.011 contributor: fullname: Ahmadi – volume: 385 start-page: 138 year: 2016 ident: 10.1016/j.ymssp.2018.03.006_b0085 article-title: A defect size estimation method based on operational speed and path of rolling elements in defective bearings publication-title: J. Sound Vib. doi: 10.1016/j.jsv.2016.09.014 contributor: fullname: Moazen-Ahmadi |
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| Snippet | •The empirical model of the entry event improves the precision to identify the entry point from the bearing vibration signal to improve estimation result.•The... This paper proposes signal processing techniques to extract entry and exit points from the bearing vibration signal for spall size estimation. The entry point... |
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| SubjectTerms | Background noise Bearings Frequency response Machine tools Roller bearings Rolling element bearing Signal processing Spall size estimation Variational Mode Decomposition (VMD) |
| Title | Signal processing techniques for rolling element bearing spall size estimation |
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