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Application of SPM for Fault Detection and RUL Estimation; Comparison with Vibration Analysis

Davoodabadi, Ali | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52262 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Behzad, Mehdi
  7. Abstract:
  8. Rolling element bearings (REBs) are one of the most critical components in rotating ma-chines. Failure of these components may lead to fatal and costly breakdowns in rotating machinery. Therefore, it is significant to detect faults at early stage accurately. The pur-pose of this study is to compare vibration analysis and shock pulse method (SPM) in early detection of fault and remaining useful life prediction of REBs. To the aim, a set of ac-celerated life tests on REBs was planned. Vibration and shock pulse values accelerated life tests of the REBs were simultaneously measured from the moment of start to the end of the failure by two vibration and shock pulse sensors and their changes were recorded. In the first part, the trend of vibration level and shock pulse level were compared for ear-ly detection of the unhealthy condition in REBs. In addition, the extracted spectrums from SPM, empirical mode decomposition, continuous wavelet transform and envelope techniques are studied to detect bearing characteristics frequencies in order to diagnostic. In the next section, a comparison is made between the features of vibration analysis and shock pulse using an artificial neural network to remaining useful life prediction of REBs. Results show that SPM has better performance on early fault detection and remaining use-ful life prediction of REBs rather than vibration analysis techniques
  9. Keywords:
  10. Remaining Useful Life ; Rolling Bearing ; Condition Monitoring ; Early Detection ; Vibrational Analysis ; Shock Pulse Method ; Fault Detection ; Artificial Neural Network

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