A framework for aerospace vehicle reasoning (FAVER)

dc.contributor.advisorJennions, Ian K.
dc.contributor.advisorSkaf, Zakwan
dc.contributor.authorEzhilarasu, Cordelia Mattuvarkuzhali
dc.date.accessioned2023-09-28T13:04:53Z
dc.date.available2023-09-28T13:04:53Z
dc.date.issued2019-10
dc.description.abstractAirliners spend over 9% of their total revenue in Maintenance, Repair, and Overhaul (MRO) and working to bring down the cost and time involved. The prime focus is on unexpected downtime and extended maintenance leading to delays in the flights, which also reduces the trustworthiness of the airliners among the customers. One of the effective solutions to address this issue is Condition based Maintenance (CBM), in which the aircraft systems are monitored frequently, and maintenance plans are customized to suit the health of these systems. Integrated Vehicle Health Management (IVHM) is a capability enabling CBM by assessing the current condition of the aircraft at component/ Line Replaceable Unit/ system levels and providing diagnosis and remaining useful life calculations required for CBM. However, there is a lack of focus on vehicle level health monitoring in IVHM, which is vital to identify fault propagation between the systems, owing to their part in the complicated troubleshooting process resulting in prolonged maintenance. This research addresses this issue by proposing a Framework for Aerospace Vehicle Reasoning, shortly called FAVER. FAVER is developed to enable isolation and root cause identification of faults propagating between multiple systems at the aircraft level. This is done by involving Digital Twins (DTs) of aircraft systems in order to emulate interactions between these systems and Reasoning to assess health information to isolate cascading faults. FAVER currently uses four aircraft systems: i) the Electrical Power System, ii) the Fuel System, iii) the Engine, and iv) the Environmental Control System, to demonstrate its ability to provide high level reasoning, which can be used for troubleshooting in practice. FAVER is also demonstrated for its ability to expand, update, and scale for accommodating new aircraft systems into the framework along with its flexibility. FAVER’s reasoning ability is also evaluated by testing various use cases.en_UK
dc.description.coursenameTransport Systemsen_UK
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20305
dc.language.isoenen_UK
dc.publisherCranfield Universityen_UK
dc.publisher.departmentSATMen_UK
dc.rights© Cranfield University, 2020. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.en_UK
dc.subjectCondition Based Maintenanceen_UK
dc.subjectVehicle health monitoringen_UK
dc.subjectDiagnosisen_UK
dc.subjectReasoningen_UK
dc.subjectAircraft systemsen_UK
dc.subjectFault propagationen_UK
dc.subjectAircraft accidentsen_UK
dc.titleA framework for aerospace vehicle reasoning (FAVER)en_UK
dc.typeThesis or dissertationen_UK
dc.type.qualificationlevelDoctoralen_UK
dc.type.qualificationnamePhDen_UK

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