A generalised methodology for the diagnosis of aircraft systems

Simple item page
dc.contributor.authorEzhilarasu, Cordelia Mattuvarkuzhali
dc.contributor.authorSkaf, Zakwan
dc.contributor.authorJennions, Ian K.
dc.date.accessioned2021-01-28T17:19:54Z
dc.date.available2021-01-28T17:19:54Z
dc.date.issued2021-01-11
dc.description.abstractAn aircraft is made up of a number of complicated systems which work in harmony to ensure safe and trouble-free flight. In order to maintain such a platform, many diagnostic and prognostic techniques have been suggested, mostly aimed at components but some at the system level. Together these form a patchwork approach to the overall problem of efficiently informing aircraft maintenance to the Original Equipment Manufacturers, the operators /airlines, and the Maintenance, Repair, and Overhaul organisations. It involves these organisations having to support several different approaches to aircraft health management, and is therefore inefficient and costly. In the current work, a streamlined methodology is put forward. This is based on OSA-CBM (Open System Architecture for Condition Based Maintenance) and can be applied to any aircraft system. Integral with this is the use of mRMR (minimum redundancy maximum relevance) for feature selection, the resulting symptom vector being used for fault diagnosis. This approach is demonstrated on three test cases: the engine, the environmental control system, and the fuel system. In each case, the digital twin setup, simulation conditions for healthy and faulty scenarios, a methodology based on OSA-CBM up to diagnostics are detailed. Diagnostics is carried out for each system in turn, using four machine learning supervised algorithms. The best performing algorithm for each system will then subsequently be used in a vehicle level reasoner called FAVER (A Framework for Aerospace Vehicle Reasoning), which requires these system diagnoses as a starting point for vehicle reasoning and fault ambiguity resolutionen_UK
dc.identifier.citationEzhilarasu CM, Skaf Z, Jennions IK. (2021) A generalised methodology for the diagnosis of aircraft systems. IEEE Access, Volume 9, 2021, pp. 11437-11454en_UK
dc.identifier.issn2169-3536
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2021.3050877
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16279
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectminimum redundancy maximum relevanceen_UK
dc.subjectdigital twinen_UK
dc.subjectOSA-CBMen_UK
dc.subjectAircraft systemsen_UK
dc.titleA generalised methodology for the diagnosis of aircraft systemsen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Generalised_methodology_for_the_diagnosis_of_aircraft_systems-2020.pdf
Size:
1.59 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)