The implementation of advanced diagnostic and prognostic concepts - Practical tools for effective diagnostic and prognostic health management

Callan, Robert; Larder, B.

doi:10.1109/aero.2003.1234160

Cited by 7 publications

(1 citation statement)

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“…Bayesian networks are an increasingly popular approach to modeling these and other forms of uncertainty inherent to prognosis, e.g., in [4,23]. Our approach is based on a particular class of Bayesian networks, with global and local structure (layered models and "noisy" nodes) that have allowed us to efficiently develop complex models allowing less stringent data requirements.…”

Section: Related Workmentioning

confidence: 99%

An Implementation of Prognosis with Dynamic Bayesian Networks

Przytula

Choi

2008

2008 IEEE Aerospace Conference

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We present a probabilistic approach to reasoning in diagnosis and prognosis. The approach represents a mathematically rigorous way of handling uncertainty, which is often present in diagnosis, but inherent to prognosis. The approach is based on a novel form of layered dynamic Bayesian network models, which is used to perform Bayesian inference. It coherently integrates evidence on component usage, environmental conditions of operation, as well as component health history. The approach has been tested on several examples of health prognosis for electromechanical and electronic subsystems in aviation. 2

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Section: Related Workmentioning

confidence: 99%

An Implementation of Prognosis with Dynamic Bayesian Networks

Przytula

Choi

2008

2008 IEEE Aerospace Conference

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A Need-focused Approach to Air Force Engine Health Management Research

Wade

2005

2005 IEEE Aerospace Conference

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Abstract-12 This paper outlines the work that the author has done to develop a structure to help direct Engine Health Management (EHM) research. It discusses the definitions of the relevant EHM terms, outlines the essential elements of an EHM system, deduces the aims of an EHM system through the contributions it can make to the top-level Air Force goals, and uses this to create an EHM vision. It then proposes a method of grouping EHM research programs in terms of their scope and offers a first order method of rating their likely impact. Finally, it raises a number of important issues that need to be considered when developing an EHM system.

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An Integrated Approach to the Development of an Intelligent Prognostic Health Management System

Callan¹,

Larder²,

Sandiford³

2006 IEEE Aerospace Conference

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The implementation of advanced diagnostic and prognostic concepts - Practical tools for effective diagnostic and prognostic health management

Cited by 7 publications

References 1 publication

An Implementation of Prognosis with Dynamic Bayesian Networks

An Implementation of Prognosis with Dynamic Bayesian Networks

A Need-focused Approach to Air Force Engine Health Management Research

An Integrated Approach to the Development of an Intelligent Prognostic Health Management System

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