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Digital image processing algorithms for automated inspection of dynamic effects in roller bearings
Author(s): Bettina Altmann; Christian Pape; Eduard Reithmeier
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Paper Abstract

Unstable movement in roller bearings like cage or roller slip can lead to damages or eventually even to an early break of the bearing. To prevent slip, inadequate operating states should be avoided. Therefore, it is necessary to study the dynamic behavior of the bearing. Unfortunately, there is only a limited range of measurement methods for the dynamic of bearing components. Two possible approaches are using solely a high-speed camera or the combination of an optomechanical image derotator and a high-speed camera. This work focuses on a proposal which is suitable for both. Initially, the influence of the rotational velocity in the images is eliminated. In the next step the measurement data is reduced to a region of interest which displays a particular rolling-element. A rolling element is equipped with a linear marker which, in the next stage, is segmented by a thresholding method to multiple regions. The region representing the marker is extracted from the background and the position is calculated by a Principle Component Analysis. Depending on the shift of the angular position and the lag time between two images, the rotational velocity of the rolling element is calculated. Thus, it is possible to determine whether the rolling element is operating under ideal conditions. In conclusion, it can be said that this approach enables a simple and flexible non-invasive method to depict the occurrence of roller slip in roller bearings.

Paper Details

Date Published: 26 June 2017
PDF: 7 pages
Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340A (26 June 2017); doi: 10.1117/12.2269065
Show Author Affiliations
Bettina Altmann, Leibniz Univ. Hannover (Germany)
Christian Pape, Leibniz Univ. Hannover (Germany)
Eduard Reithmeier, Leibniz Univ. Hannover (Germany)


Published in SPIE Proceedings Vol. 10334:
Automated Visual Inspection and Machine Vision II
Jürgen Beyerer; Fernando Puente León, Editor(s)

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