Estimation of uncertainty in the structure-borne sound power transmission from a source to a receiver

Evans, T

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.

Citation

Evans, T. Estimation of uncertainty in the structure-borne sound power transmission from a source to a receiver. (Thesis). Salford : University of Salford

• Thesis Type: Thesis
• Deposit Date: Oct 3, 2012
• Award Date: Jan 1, 2010