Prediction models showing effects of design parameters on induction machine cooling fan performance and sound power

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    Cooling fan noise is the most significant part of the noise emission of an induction machine. An experimental study was carried out to study the effects of installation parameters on the noise emission of the cooling fan. A series of tests was done according to a test plan designed by a design of experiments method. The factors under investigation were the tip-clearance, the axial position of the impeller and the distance between the impeller and the motor. Experimental prediction models of the results are used to illustrate the changes in the performance and specific sound power level curves of the fan as a function of the parameters. Prediction models are presented for the 1/3 octave-band frequency spectra. The effects of the tip clearance on the curves are the most significant and similar at all operating points of the fan. The effects of the other two factors vary depending on the operation point. The effects on the sound power spectrum depend on the parameter varied. The clearest differences can be seen when the tip clearance is used as a parameter.
    Original languageEnglish
    Title of host publicationProceedings of Inter-Noise 2002, the International Congress and Exposition on Noise Control Engineering
    PublisherInstitute of Noise Control Engineering
    Number of pages6
    Publication statusPublished - 2002
    MoE publication typeNot Eligible
    EventInternational Congress and Exposition on Noise Control Engineering, Inter-Noise 2002 - Dearborn, United States
    Duration: 19 Aug 200221 Aug 2002

    Conference

    ConferenceInternational Congress and Exposition on Noise Control Engineering, Inter-Noise 2002
    CountryUnited States
    CityDearborn
    Period19/08/0221/08/02

    Keywords

    • induction machine
    • fan noise
    • cooling fan
    • prediction model

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