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Proceedings Paper

Intelligent approach to prognostic enhancements of diagnostic systems
Author(s): George Vachtsevanos; Peng Wang; Noppadon Khiripet; Ash Thakker; Thomas R. Galie
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Paper Abstract

This paper introduces a novel methodology to prognostics based on a dynamic wavelet neural network construct and notions from the virtual sensor area. This research has been motivated and supported by the U.S. Navy's active interest in integrating advanced diagnostic and prognostic algorithms in existing Naval digital control and monitoring systems. A rudimentary diagnostic platform is assumed to be available providing timely information about incipient or impending failure conditions. We focus on the development of a prognostic algorithm capable of predicting accurately and reliably the remaining useful lifetime of a failing machine or component. The prognostic module consists of a virtual sensor and a dynamic wavelet neural network as the predictor. The virtual sensor employs process data to map real measurements into difficult to monitor fault quantities. The prognosticator uses a dynamic wavelet neural network as a nonlinear predictor. Means to manage uncertainty and performance metrics are suggested for comparison purposes. An interface to an available shipboard Integrated Condition Assessment System is described and applications to shipboard equipment are discussed. Typical results from pump failures are presented to illustrate the effectiveness of the methodology.

Paper Details

Date Published: 20 July 2001
PDF: 11 pages
Proc. SPIE 4389, Component and Systems Diagnostics, Prognosis, and Health Management, (20 July 2001); doi: 10.1117/12.434227
Show Author Affiliations
George Vachtsevanos, Georgia Institute of Technology (United States)
Peng Wang, Georgia Institute of Technology (United States)
Noppadon Khiripet, Georgia Institute of Technology (United States)
Ash Thakker, Global Technology Connection (United States)
Thomas R. Galie, Naval Surface Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 4389:
Component and Systems Diagnostics, Prognosis, and Health Management
Peter K. Willett; Thiagalingam Kirubarajan, Editor(s)

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