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Proceedings Paper

Reasoning and modeling systems in diagnosis and prognosis
Author(s): Amit Mathur; Kevin F. Cavanaugh; Krishna R. Pattipati; Peter K. Willett; Thomas R. Galie
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Paper Abstract

Diagnosis and prognosis are processes of assessment of a system's health - past, present and future - based on observed data and available knowledge about the system. Due to the nature of the observed data and the available knowledge, the diagnostic and prognostic methods are often a combination of statistical inference and machine learning methods. The development (or selection) of appropriate methods requires appropriate formulation of the learning and inference problems that support the goals of diagnosis and prognosis. An important aspect of the formulation is modeling - relating the real system to its mathematical abstraction. The models, depending on the application and how well it is understood, can be either empirical or scientific (physics based). The expression of the model, too, tends to be statistical (probabilistic) to account for uncertainties and randomness. This paper explores the impact of diagnostic and prognostic goals on modeling and reasoning system requirements, with the purpose of developing a common software framework that can be applied to a large class of systems. In particular, the role of failure-dependency modeling in the overall decision problem is discussed. The applicability of Qualtech Systems' modeling and diagnostic software tools to the presented framework for both the development and implementation of diagnostics and prognostics is assessed. Finally, a potential application concept for advancing the reliability of Navy shipboard Condition Based Maintenance (CBM) systems and processes is discussed.

Paper Details

Date Published: 20 July 2001
PDF: 10 pages
Proc. SPIE 4389, Component and Systems Diagnostics, Prognosis, and Health Management, (20 July 2001); doi: 10.1117/12.434239
Show Author Affiliations
Amit Mathur, Qualtech Systems, Inc. (United States)
Kevin F. Cavanaugh, Qualtech Systems, Inc. (United States)
Krishna R. Pattipati, Qualtech Systems, Inc. (United States)
Peter K. Willett, Univ. of Connecticut (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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