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Proceedings Paper

Useful lifetime tracking via the IMM
Author(s): Ethan Phelps; Peter K. Willett; Thiagalingam Kirubarajan
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Paper Abstract

Inference of the expected time-to-failure is made difficult by the need to track and predict the trajectories of real-valued system parameters over essentially unbounded domains, and by the need to identify a subset of these domains that refers to a state of unsafe operation. In a previous paper we proposed a novel technique whereby these problems are avoided: instead of physical system or sensor parameters, sensor-level test-failure probability vectors (bounded within the unit hypercube) are tracked; and via a close relationship with the TEAMS suite of modeling tools, the terminal states for all such vectors can be enumerated. In that paper a full-dimension Kalman filter and IMM (interacting multiple model) tracking solution was proposed, but results were preliminary. In this paper we continue, modify, and provide reasonably convincing results.

Paper Details

Date Published: 16 July 2002
PDF: 12 pages
Proc. SPIE 4733, Component and Systems Diagnostics, Prognostics, and Health Management II, (16 July 2002); doi: 10.1117/12.475504
Show Author Affiliations
Ethan Phelps, Univ. of Connecticut (United States)
Peter K. Willett, Univ. of Connecticut (United States)
Thiagalingam Kirubarajan, McMaster Univ. (Canada)


Published in SPIE Proceedings Vol. 4733:
Component and Systems Diagnostics, Prognostics, and Health Management II
Peter K. Willett; Thiagalingam Kirubarajan, Editor(s)

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