Using artificial intelligence for data reduction in mechanical engineering

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dc.creatorMdlazi, L.
dc.creatorStander, C. J.
dc.creatorHeyns, P. S.
dc.creatorMarwala, T.
dc.date2007-05-11
dc.date.accessioned2026-07-07T08:00:58Z
dc.date.available2026-07-07T08:00:58Z
dc.descriptionIn this paper artificial neural networks and support vector machines are used to reduce the amount of vibration data that is required to estimate the Time Domain Average of a gear vibration signal. Two models for estimating the time domain average of a gear vibration signal are proposed. The models are tested on data from an accelerated gear life test rig. Experimental results indicate that the required data for calculating the Time Domain Average of a gear vibration signal can be reduced by up to 75% when the proposed models are implemented.
dc.description6 pages
dc.identifierhttps://arxiv.org/abs/0705.1673
dc.identifierhttp://arxiv.org/abs/0705.1673
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/128810
dc.subjectComputational Engineering, Finance, and Science
dc.subjectArtificial Intelligence
dc.subjectNeural and Evolutionary Computing
dc.titleUsing artificial intelligence for data reduction in mechanical engineering
dc.typetext

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