A framework for the propagation of uncertainty in Transfer Path Analysis

Abstract Transfer Path Analysis (TPA) is a test-based methodology used to analyse the propagation of noise and vibration in complex systems. In this paper we present a covariance based framework for the propagation of experimental uncertainty in classical, blocked force, and component-based TPA procedures. The presence of both complex and correlated uncertainty is acknowledged through a bivariate description of the underlying uncertainty. The framework is summarised by a series of equations that propagate uncertainty through the various stages of a TPA procedure i.e. inverse source characterisation, dynamic sub-structuring, and forward response prediction. The uncertainty associated with rank ordering of source contributions is also addressed. To demonstrate the proposed framework a numerical simulation is presented, the results of which are compared against Monte-Carlo methods with good agreement obtained. An experimental study is also presented, where a blocked force TPA is performed on an electric steering system. The proposed uncertainty framework requires no additional experimental effort over and above what is performed in a standard TPA and may therefore be readily implemented into current TPA practices.