Daniel Ainalis

Estimating the ride quality characteristics of vehicles with random decrement analysis of on-the-road vibration response data

ABSTRACT This paper describes the application of a practical analytical technique based on the random decrement method to estimate the rigid sprung mass dynamic characteristics (frequency response function) of road vehicles using only vibration response data during constant-speed operation. A brief history and development of the random decrement technique is presented, along with a summary of work undertaken on optimal parameter selection to establish the random decrement signature. Two approaches to estimate the dynamic characteristics from the random decrement signature are described and evaluated. A custom, single-wheeled vehicle (physical quarter car) was commissioned to undertake a series of on-the-road experiments at various nominally constant operating speeds. The vehicle, also instrumented as an inertial profilometer, simultaneously measured the longitudinal pavement profile to establish the vehicles actual dynamic characteristics during operation. The main outcome of the paper is that the random decrement technique can be used to provide accurate estimates of the sprung mass mode of the vehicles dynamic characteristics for both linear and nonlinear suspension systems of an idealised vehicle.

A multi-resolution time domain technique for monitoring fatigue progression in elements subjected to random loads

Abstract Materials and structures subjected to random loading can deteriorate in a complex fashion. A technique for monitoring the manner in which this decay occurs can be useful, not in the least, for comparative analysis. One method for monitoring structural deterioration is to continually track variations in the system’s modal parameters. Modal parameters are often extracted using the system’s frequency response function, obtained using the Fourier transform. However, for continual parameter extraction, the Fourier transform requires that a compromise be made between the spectral accuracy of the estimates and how frequently they can be obtained. This compromise significantly limits the potential of Fourier transform based techniques as continuous structural integrity assessment tools. The technique presented herein applies the Hilbert transform to the system’s instantaneous impulse response function, captured using the coefficients of an adaptive finite-impulse-response filter, in order to continually monitor shifts in the system’s natural frequency. This approach allows for the properties of systems to be evaluated at regular intervals without compromising spectral uncertainty. Numerous damage scenarios were performed (using both physical and numerical systems) in order to test the sensitivity of the technique as well as its ability to converge with changes in system characteristics.