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Lifetime Prediction of Rolling Element Bearings using Adaptive Algorithms Based on their Vibration Trends

Alandi Hallaj, Ahmad | 2009

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 39425 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Behzad, Mehdi
  7. Abstract:
  8. Rolling element bearings are the most widely used components in rotating machinery and so, estimation of their remaining useful lifetime in order to increase the reliability and availability of them is a critical issue in the field of condition monitoring of these machinery. Despite numerous researches which have tried to develop a model for precise prediction of rolling element bearings’ lifetime, there is no method which can predict their remaining lifetime exactly. The failure criterion in these components is the area of defect in their races and rolling elements. Consequently, an approach which can predict the defect area of these components is susceptible to prediction of their remaining lifetime. In this study a method to predict the defect area of rolling element bearings is proposed using RLS adaptive algorithms and fatigue damage mechanics relations. First, two patterns are developed to correlate the statistical features of vibration signals and the defect size on inner an outer races. Having developed these patterns, healthy bearings are tested under the operating conditions and the vibration data is collected from the beginning of defect until the final failure. Using adaptive algorithms, the existing parameters in the mechanistic relations are updated and the defect area of defect can be predicted. The results of experimental tests show that this approach can determine the defect area and as a result, the remaining lifetime of rolling element bearings can be predicted reliably. Furthermore, a new approach to determine the defect size of rolling element bearings is proposed. This approach is based on the statistical characteristics of the vibrations signals generated by rolling element bearings. For the first time in this study the level crossing rate is introduced as a suitable parameter for rolling bearing defect size estimation. The acceleration signal of roller bearings has been measured and crossing analysis showed that the number of crossings is proportional to the defect size on inner and outer races. The results of experimental tests proved that this parameter can determine the defect length of rolling bearings with a good approximation
  9. Keywords:
  10. Rolling Bearing ; Vibration ; Adaptive Algorithm ; Life Time Estmation ; Experimental Test ; Defect Size

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