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Integrated Predictive Diagnostics: An Expanded View FREE

[+] Author Affiliations
Robert J. Hansen, David L. Hall, G. William Nickerson, Shashi Phoha

The Pennsylvania State University, State College, PA

Paper No. 96-GT-034, pp. V005T15A006; 10 pages
doi:10.1115/96-GT-034
From:
  • ASME 1996 International Gas Turbine and Aeroengine Congress and Exhibition
  • Volume 5: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; Education; General
  • Birmingham, UK, June 10–13, 1996
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-7876-7
  • Copyright © 1996 by ASME

abstract

In a previous paper (Hansen et al., 1995), a conceptual framework for developing a true prognostic or predictive diagnostic capability was described. The current paper expands on this framework by describing micro-mechanical and dynamic models, sensors and data fusion, signal processing, approximate reasoning, distributed architecture, and human factors research and development being conducted to provide such a capability for a broad range of applications. These include both autonomous and man-in-the-loop decision making about maintenance actions and local and geographically distributed monitoring and data analysis architectures.

Copyright © 1996 by ASME
This article is only available in the PDF format.

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