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Model Based Spur Gear Failure Prediction Using Gear Diagnosis

[+] Author Affiliations
Sukhwan Choi

GE Energy

C. James Li

Rensselaer Polytechnic Institute

Paper No. IMECE2005-82482, pp. 819-823; 5 pages
doi:10.1115/IMECE2005-82482
From:
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Manufacturing Engineering and Materials Handling, Parts A and B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Manufacturing Engineering Division and Materials Handling Division
  • ISBN: 0-7918-4223-1 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME

abstract

Gears are common mechanical components used in power transmissions and frequently responsible for transmission failures. Since the crack size is not directly measurable while gear is in service, there is difficulty in predicting residual life of gears in service. The aim of this study is to present a prognostic methodology to predict the residual life of a cracked spur gear that is in service utilizing 2D FEM/fracture mechanics based failure model. The previously developed gear diagnostic algorithms and artificial neural network were employed to estimate crack size from measured gear vibration. The predicted results were validated with experimental data. Experimental results showed that the method had an averaged error of 12.94% in its estimate of remaining life.

Copyright © 2005 by ASME

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