Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets

Abstract

Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of a vehicle in time domain), the frequency analysis (identification of the parameters of the crash pulse in frequency domain), and the time–frequency analysis, which comprises those techniques that study a signal in both the time and frequency domains simultaneously, using Morlet wavelet properties. Determination of time of occurrence of particular frequency components included in the measured acceleration pulse and further analysis of the obtained scalegram are based on the reproduction of each crash pulse component, according to the frequencies identified in the acceleration signal. Finally, by using the superposition principle, those major signal components are combined, yielding the reproduced crash pulse. The comparative analysis between the current method's outcome, the responses of models established previously by using different approach and the behavior of a real car is performed and reliability of the actual methods and tools is evaluated.