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Toward a methodology of requirements definition for prognostics and health management system to support aircraft predictive maintenance

journal contribution
posted on 2024-11-02, 13:46 authored by Rui Li, Wilhelmus VerhagenWilhelmus Verhagen, Richard Curran
Aircraft maintenance has been further developed with predictive maintenance instead of solely condition-based maintenance. Prognostics and health management (PHM) with advanced technologies can utilize real-time and historical health state information to provide actionable information, enabling predictive maintenance decision-making. In this case, the methodology of how to design the PHM systems is an issue to be faced. The state of the art has provided several conceptual design methodologies and associated methods to support the conceptual requirements development of PHM systems. However, there is no rigorous process available for requirements definition. Existing options for requirements derivation are lacking details, which restricting PHM system design and development. This constitutes a major drawback and hurdle towards the successful design of PHM systems in practice. This paper consequently proposes a methodology for the systematic derivation of system requirements towards PHM system development. Besides, this methodology defines detailed processes for requirements definition, and positions mean through which various categories of requirements can be derived through appropriate analyses in detail. Sequences of interoperability requirements categories and associated flow-down perspectives are identified. To evaluate the applicability, this paper undertakes the case study of requirements definition for a generic PHM system, which provides a comprehensive application of the methodology. Designers can perform requirements definition under this methodology as guidance towards the design of a successful PHM system, providing solutions for predicting remaining useful life (RUL) to support aircraft predictive maintenance.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.ast.2020.105877
  2. 2.
    ISSN - Is published in 12709638

Journal

Aerospace Science and Technology

Volume

102

Number

105877

Start page

1

End page

20

Total pages

20

Publisher

Elsevier

Place published

France

Language

English

Copyright

© 2020 Elsevier Masson SAS. All rights reserved.

Former Identifier

2006100830

Esploro creation date

2020-09-08

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