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Research Papers

Singular Spectrum Analysis for Bearing Defect Detection

[+] Author and Article Information
Bovic Kilundu

Risks Research Centre, University of Mons, 20 Place du Parc, 7000 Mons, Belgiumbovic.kilundu@umons.ac.be

Xavier Chiementin

 University of Reims, GRESPI BP 1039, 51687 Reims Cedex 2, France

Pierre Dehombreux

Department of Mechanical Engineering, Risks Research Centre, University of Mons, 20 Place du Parc, 7000 Mons, Belgium

J. Vib. Acoust 133(5), 051007 (Sep 20, 2011) (7 pages) doi:10.1115/1.4003938 History: Received May 06, 2010; Revised March 26, 2011; Published August 31, 2011; Online September 20, 2011

In this work, singular spectrum analysis is employed to process vibration signals resulting from rolling bearings. A monitoring indicator is defined from the fact that the structure of a signal recorded from a bearing becomes more complex when the bearing becomes defective. This can be explained by the nonstationarity and the nonlinearity induced by the defect. The effects of operating parameters such as load and speed on the indicator are studied. Results demonstrate that the indicator defined in this paper is less sensitive to these parameters than the rms value, a traditional vibratory indicator.

Copyright © 2011 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Cascade two-level decomposition

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Figure 3

Decomposition of a signal resulting from a healthy bearing

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Figure 4

Decomposition of a signal resulting from a defective bearing

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Figure 5

Signals resulting from a healthy and a damaged bearing

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Figure 6

Evolution of the number of significant components with the proportion of variance

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Figure 7

Effect of the sampling frequency on the NPC75 for different defect sizes

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Figure 8

Signal resulting from bearing with 8 mm2 outer race defect. From top to bottom data from channels 1–4 are represented.

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Figure 9

Effect of load and speed on the NPC75 (channel 1 and 2) for different defect sizes

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Figure 10

Effect of load and speed on the NPC75 (channel 3 and 4) for different defect sizes

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Figure 11

Evolution of the NPC75 indicator with the bearing damage

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Figure 12

Comparison of the load and speed effects on NPC75 and on the rms value

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Figure 13

Direct spectrum of a damaged bearing. The bearing defect component is masked

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Figure 14

Envelope spectrum of a damaged bearing

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Figure 15

Indicator from envelope analysis

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