Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.524000
Title: Estimation of uncertainty in the structureborne sound power transmission from a source to a receiver
Author: Evans, T. A.
ISNI:       0000 0004 2691 8311
Awarding Body: University of Salford
Current Institution: University of Salford
Date of Award: 2010
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Abstract:
Uncertainty in structural dynamics is of growing concern to numerous industries. Significant attention has previously been devoted to the study of frequency response functions, however the uncertainty associated with excitation of structures by structureborne sound sources has received little attention. In this work, the uncertainty in the structure borne sound power transmitted from a vibration source into a receiving structure is considered. A method is presented whereby the uncertainties in the active and dynamic properties of a structure borne sound source and its receiver structure are propagated through to the injected power. Consideration is given to the case where the data describing the source and receiver is incomplete and is therefore termed ‘granular’. An approach for the estimation of the mean and uncertainty of granular variables is developed and it is shown that by estimating the mean and uncertainty of the missing elements the uncertainty propagation approach can be used for a ‘granular’ case. This approach is illustrated using an example in which the free velocity phase data is assumed to be unavailable. Idealised structure borne sound sources are created analytically in order to examine the validity of the presented methods. Good correlation is observed between the estimated uncertainties in the transmitted power and the uncertainties obtained through a Monte Carlo analysis. Insight into the frequency regions where large uncertainties can be expected in the transmitted structure borne sound power is obtained. It is argued that by providing estimates for the uncertainty of a prediction of the transmitted power, an insight into the reliability of the estimate is achieved, allowing engineering decisions to be made with greater confidence.
Supervisor: Not available Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.524000  DOI: Not available
Keywords: QA275 Mathematical Statistics ; QC221-246 Acoustics - Sound
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