Design optimization of power generator soundproofing enclosure using genetic algorithm tool

dc.contributor.authorEhelepola, I
dc.contributor.authorChandima, DP
dc.date.accessioned2018-05-09T20:52:37Z
dc.date.available2018-05-09T20:52:37Z
dc.description.abstractThis paper introduces a numerical method for optimally designing a passive noise control enclosure for depressing air borne noise of reciprocating engine type power generators. Sound pressure level of soundproofed power generator has been modeled using sound pressure level of unenclosed power generator and insertion loss of passive enclosure. In this context, mathematically developed acoustic equation optimized for the design variables of dimensions, panel material properties and thickness of enclosures under constrains of sound pressure level, cost, weight, and size of enclosures. Genetic Algorithm tool was used for optimization and it has developed in MATLAB software. The developed optimized model has validated by designing and fabricating a passive enclosure for a diesel power generator with a capacity of 22kVA. Eventually the developed design procedure is giving a simple and fast design tool with Graphical User Interface run in MATLAB to provide locally optimized enclosure design parameter which can be used for conceptualize the enclosure design.en_US
dc.identifier.conference110th Annual sessions of the Institution of Engineers, Sri Lankaen_US
dc.identifier.departmentDepartment of Mechanical Engineeringen_US
dc.identifier.facultyEngineeringen_US
dc.identifier.pgnosp. 267-274en_US
dc.identifier.proceeding110th Annual sessions transactions 2016 part B : technical papersen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/13090
dc.identifier.year2016en_US
dc.language.isoenen_US
dc.subjectPassive Noise Controlen_US
dc.subjectSound Pressure Levelen_US
dc.subjectInsertion Lossen_US
dc.subjectClose-fitting enclosureen_US
dc.subjectGenetic Algorithm toolen_US
dc.titleDesign optimization of power generator soundproofing enclosure using genetic algorithm toolen_US
dc.typeConference-Abstracten_US

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