A system-level failure propagation detectability using ANFIS for an aircraft electrical power system

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dc.contributor.authorEzhilarasu, Cordelia Mattuvarkuzhali
dc.contributor.authorJennions, Ian K.
dc.date.accessioned2020-04-23T09:13:35Z
dc.date.available2020-04-23T09:13:35Z
dc.date.issued2020-04-20
dc.description.abstractThe Electrical Power System (EPS) in an aircraft is designed to interact extensively with other systems. With a growing trend towards more electric aircraft, the complexity of interactions between the EPS and other systems has grown. This has resulted in an increased necessity of implementing health monitoring methods like diagnosis and prognosis of the EPS at the systems level. This paper focuses on developing a diagnostic algorithm for the EPS to detect and isolate faults and their root causes that occur at the Line Replaceable Units (LRUs) connecting with aircraft systems like the engine and the fuel system. This paper aims to achieve this in two steps: (i) developing an EPS digital twin and presenting the simulation results for both healthy and fault scenarios, (ii) developing an Adaptive Neuro-Fuzzy Inference System (ANFIS) monitor to detect faults in the EPS. The results from the ANFIS monitor are processed in two methods: (i) a crisp boundary approach, and (ii) a fuzzy boundary approach. The former approach has a poor misclassification rate; hence the latter method is chosen to combine with causal reasoning for isolating root causes of these interacting faults. The results from both these methods are presented through examples in this paper.en_UK
dc.identifier.citationEzhilarasu CM, Jennions IK. (2020) A system-level failure propagation detectability using ANFIS for an aircraft electrical power system. Applied Sciences, Volume 10, Issue 8, April 2020, Article number 2854en_UK
dc.identifier.issn2076-3417
dc.identifier.urihttps://doi.org/10.3390/app10082854
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15407
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectElectrical Power Systemen_UK
dc.subjectANFISen_UK
dc.subjectcausal reasoningen_UK
dc.subjectdiagnosisen_UK
dc.subjectfault propagationen_UK
dc.subjectaircraften_UK
dc.subjectdigital twinen_UK
dc.titleA system-level failure propagation detectability using ANFIS for an aircraft electrical power systemen_UK
dc.typeArticleen_UK

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