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A Methodology to Estimate Degradation and Reliability Based on Artificial Neural Networks

[+] Author Affiliations
Enrique A. Susemihl, Shuzhen Xu

FM Global

Paper No. IMECE2005-79993, pp. 57-61; 5 pages
doi:10.1115/IMECE2005-79993
From:
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Engineering/Technology Management
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Engineering and Technology Management Group
  • ISBN: 0-7918-4230-4 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME

abstract

Failure modes associated with degradation or ageing affect most equipment, and the estimates of failure due to them are particularly important in deciding repair or replacement. A methodology is presented here to relate physical variables with a degradation measure by using artificial neural networks to capture data and experience, and to use this degradation measure to estimate probabilities of failure. This methodology has been applied to transformers to estimate probabilities of failure due to the degradation of paper insulation, and some preliminary results are presented. These results show that the method can provide reasonable estimates.

Copyright © 2005 by ASME

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