Intelligent condition monitoring systems for unmanned aerial vehicle robots

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dc.contributor.authorAnvar, A.
dc.contributor.authorDowling, T.
dc.contributor.authorPutland, T.
dc.contributor.authorAnvar, A.
dc.contributor.authorGrainger, S.
dc.date.issued2012
dc.description.abstractThis paper presents the application of Intelligent Techniques to the various duties of Intelligent Condition Monitoring Systems (ICMS) for Unmanned Aerial Vehicle (UAV) Robots. These Systems are intended to support these Intelligent Robots in the event of a Fault occurrence. Neural Networks are used for Diagnosis, whilst Fuzzy Logic is intended for Prognosis and Remedy. The ultimate goals of ICMS are to save large losses in financial cost, time and data.
dc.description.statementofresponsibilityA. P. Anvar, T. Dowling, T. Putland, A. M. Anvar, and S. Grainger
dc.identifier.citationProceedings of the World Academy of Science, Engineering and Technology, 2012; 70:1402-1408
dc.identifier.issn2010-3778
dc.identifier.orcidGrainger, S. [0000-0003-4664-7320]
dc.identifier.urihttp://hdl.handle.net/2440/77023
dc.language.isoen
dc.publisherWASET
dc.rightsCopyright status unknown
dc.source.urihttp://www.waset.org/journals/waset/v70/v70-113.pdf
dc.subjectIntelligent Techniques, Condition Monitoring Systems, ICMS
dc.subjectRobots
dc.subjectFault
dc.subjectUnmanned Aerial Vehicle
dc.subjectUAV
dc.subjectNeural Networks
dc.subjectDiagnosis
dc.subjectFuzzy Logic
dc.subjectPrognosis
dc.subjectRemedy.
dc.titleIntelligent condition monitoring systems for unmanned aerial vehicle robots
dc.typeJournal article
pubs.publication-statusPublished

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