Modelling of noise due to impulsive excitation using nonlinear time series analysis

Abstract

Early acoustic machine design phases should target safety and comfort requirements, minimising the risk of hearing damage and noise exposure and ensuring a pleasant machine sound. Therefore, physical mechanisms of sound generation, propagation and radiation need to be modelled. Today, nonlinear physical relations in vibroacoustic models such as contact problems are mostly linearised. The aim of this paper is to increase the prediction quality of vibroacoustic models so that physical mechanisms behind sound generation due to complex physical, nonlinear phenomena can be better understood. The focus is on sound generation due to impulsive excitation, which is a significant sound generation mechanism in machinery, e.g. considering gears, forming processes (e.g. punching), or road loads of vehicles. We describe a model setup to simulate impulsive excitation on a laboratory scale, where structural vibrations can be analysed. Physical correlations including nonlinear correlations could be identified using nonlinear time series analysis. Recurrence plots will be used to identify features such as phase space contraction, e.g. to identify damping. These features form the basis to deepen the physical understanding of machinery noise, to contribute to enhanced acoustic machine designs and to enhance data-driven modelling using sparse regression in future research.