A systematic methodology for Prognostic and Health Management system architecture definition

Rui Li, Wim J.C. Verhagen and Richard Curran

Reliability Engineering and System Safety, 2020, vol. 193, issue C

Abstract: Prognostic and Health Management (PHM) systems support aircraft maintenance through the provision of diagnostic and prognostic capabilities, leveraging the increased availability of sensor data on modern aircraft. Diagnostics provide the functionalities of failure detection and isolation, whereas prognostics can predict the remaining useful life (RUL) of the system. In literature, PHM technologies have been studied from different perspectives, covering various aims such as improving aircraft system reliability, availability, safety and reducing the maintenance cost. From a design perspective, several conceptual formulations of design methodologies are available, enabling a set of PHM system architectures based on different frameworks and the derivation of system requirements. However, a systematic methodology towards a consistent definition of PHM architectures has not been well established. The characteristics of architectures have not been dealt with in depth. To address these gaps, this paper presents a systematic methodology for PHM architecture definition to ensure a more complete and consistent design during the development phase of the product lifecycle. Moreover, a generic PHM architecture in accordance with this systematic methodology is proposed in this article. A case study is conducted to verify and validate the architecture, ensuring it meets the requirements for a correct and complete representation of PHM characteristics.

Keywords: Prognostic and Health Management (PHM); System architecture; System engineering (SE); Aircraft maintenance (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:193:y:2020:i:c:s0951832018315084

DOI: 10.1016/j.ress.2019.106598

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