Embedded Reasoning Supporting Aerospace IVHM

Schoeller, M.; Roemer, Michael; Leonard, Matthew S; Derriso, Mark M.

doi:10.2514/6.2007-2820

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…IVHM is seen as a capability to support condition-based maintenance, 63 allowing intelligent and suitable decisions to be made based on present and future vehicle conditions. 10 It has been applied in four primary areas across the aerospace industry 57 : diagnostics, prognostics, automated inspections, and anomaly detection.…”

Section: Ivhm and Its Implementation Across Industriesmentioning

confidence: 99%

“…Managing the health of physical assets, like in the approaches mentioned Table 5, provides useful information for maintenance, but to assist an operational decision, the IVHM system might need a high-level reasoner to deduce that system’s criticality to the functioning of the entire asset. 63 Establishing the health of systems can be categorised under: (1) system health index-based, (2) integration of components’ remaining useful life (RUL), (3) influenced component-based, and (4) multiple failure modes approaches. 112 The health index (HI) of a component can be defined by the ‘functional availability’ of that component to execute the intended purpose for which it was made.…”

Section: Health Index (Hi) For Operational Decisionsmentioning

confidence: 99%

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Platform health management for aircraft maintenance – a review

Kwakye,

Jennions,

Ezhilarasu

2024

Proceedings of the Institution of Mechanical Engineers, Part G:

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Aircraft health management has been researched at both component and system levels. In instances of certain aircraft faults, like the Boeing 777 fuel icing problem, there is evidence suggesting that a platform approach using an Integrated Vehicle Health Management (IVHM) system could have helped detect faults and their interaction effects earlier, before they became catastrophic. This paper reviews aircraft health management from the aircraft maintenance point of view. It emphasizes the potential of a platform solution to diagnose faults, and their interaction effects, at an early stage. The paper conducts a thorough analysis of existing literature concerning maintenance and its evolution, delves into the application of Artificial Intelligence (AI) techniques in maintenance, explains the rationale behind their employment, and illustrates how AI implementation can enhance fault detection using platform sensor data. Further, it discusses how computational severity and criticality indexes (health indexes) can potentially be complementary to the use of AI for the provision of maintenance information on aircraft components, for assisting operational decisions.

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Section: Ivhm and Its Implementation Across Industriesmentioning

confidence: 99%

Section: Health Index (Hi) For Operational Decisionsmentioning

confidence: 99%

Platform health management for aircraft maintenance – a review

Kwakye,

Jennions,

Ezhilarasu

2024

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…Moni-tors (Benowitz, 2014) are code within a fault identification system that is responsible for detecting anomalous situations or behavior. Similarly, Monitor-Based Oracles provide ways of both capturing and evaluating possible fault occurrence (Yen et al, 2017;Abel et al, 2013;Schoeller et al, 2007).…”

Section: Physics-based Model-driven Diagnosticsmentioning

confidence: 99%

Finding faults: A scoping study of fault diagnostics for Industrial Cyber–Physical Systems

Dowdeswell

Sinha

MacDonell

2020

Journal of Systems and Software

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…Currently, in the aerospace field, the research of integrated system health management has attracted wide attention. The study emphasis includes the logic architecture of health management [1], reasoner technology [2][3][4][5], and sensor selection. Besides that content about vehicle health management, mission health management is also researched.…”

Section: Introductionmentioning

confidence: 99%

The Preliminary Research on Health Management of Stratospheric Airship

Huang

Xia

Zeng

2011

AMM

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The stratospheric airship, with long-endurance and quasi-static capability, is suitable to carry out special mission such as communications relay, hot spots monitoring, etc. In order to improve the safety performance of the stratospheric airship and keep the robustness of mission, health management (HM) system is introduced, the foundation of which is the logic architecture. Based on the analysis of three options about the logic architecture used in spacecraft, hierarchical fusion architecture is selected, the functional modules in which are designed in detail. To solve urgent faults, moreover, the autonomous intelligent control system (AICS) is introduced. Meanwhile, monitoring mission is taken as an example to discuss the mission health management strategy based on laser communication.

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Embedded Reasoning Supporting Aerospace IVHM

Cited by 6 publications

References 3 publications

Platform health management for aircraft maintenance – a review

Platform health management for aircraft maintenance – a review

Finding faults: A scoping study of fault diagnostics for Industrial Cyber–Physical Systems

The Preliminary Research on Health Management of Stratospheric Airship

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