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Rotor Transverse Crack Detection and Diagnosis Using Embedded Modeling

[+] Author Affiliations
Kristoffer K. McKee, C. James Li

Rensselaer Polytechnic Institute, Troy, NY

Paper No. IMECE2003-43504, pp. 149-154; 6 pages
  • ASME 2003 International Mechanical Engineering Congress and Exposition
  • Manufacturing
  • Washington, DC, USA, November 15–21, 2003
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 0-7918-3720-3 | eISBN: 0-7918-4663-6, 0-7918-4664-4, 0-7918-4665-2
  • Copyright © 2003 by ASME


This study proposes an embedded modeling methodology for identifying the crack-induced local stiffness reduction in a shaft from its horizontal and vertical vibrations. An embedded model integrating a dynamic model of the rotor system, and the unknown local stiffness reduction in the form of a universal function approximator i.e., neural network, is established. As a FEM model, it can describe rotors of complex geometry. A solution method is then established to identify the local stiffness reduction of the shaft due to a crack. Subsequently, a method is then used to find the location and size of the crack along the shaft. Simulated studies were conducted to demonstrate that the crack induced stiffness reduction of a Jeffcott rotor system can be identified, and the location, size and shape of the crack can be estimated by the proposed method with high level of accuracy.

Copyright © 2003 by ASME



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