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Fault Detection With NURBs-Based Metamodels

[+] Author Affiliations
Cameron J. Turner

Los Alamos National Laboratory, Los Alamos, NM

Abiola M. Ajetunmobi, Richard H. Crawford

University of Texas at Austin, Austin, TX

Paper No. DETC2006-99637, pp. 439-450; 12 pages
doi:10.1115/DETC2006-99637
From:
  • ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 3: 26th Computers and Information in Engineering Conference
  • Philadelphia, Pennsylvania, USA, September 10–13, 2006
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4257-8 | eISBN: 0-7918-3784-X
  • Copyright © 2006 by ASME

abstract

Developing the ability for a system to self-monitor its condition is a desirable feature in many modern engineering systems. This capability facilitates a maintenance-as-needed rather than a maintenance-as-scheduled paradigm, offering potential efficiency improvements and corresponding cost savings. By using continuously updated Non-Uniform Rational B-spline (NURBs) metamodels of system performance to monitor the system condition, the onset of incipient faults can be detected by comparison to a self-generated as-built system metamodel, providing a basis for determining off-normal operating conditions. This capability is demonstrated for three distinct fault conditions prevalent in brushless DC motors. The results show that this technique can be used to develop an as-built system metamodel, develop a current system model during system operation, and detect the presence of an incipient fault condition despite the compensation provided by a feedback control system.

Copyright © 2006 by ASME

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