Abstract
Analysis of vibration of the vehicle on the road surface is of importance for cargo and vehicle security. The vibration data analysed in this paper include vibrations in three directions: longitudinal, transverse and vertical. They have been collected for military cargo during transport on various road surfaces. Compared to previous publications, in this paper, a wavelet transform is proposed for vibration analysis, with the emphasis on their efficiency and the capability to recognise important details of the signal. A series of simulations is needed for making an appropriate chose of wavelets, in order to analyse the most wanted features in time-frequency domain. Wavelet coefficients can be analysed for a wide range of frequencies. The main purpose of this study is to extract from the obtained scalograms essential features allowing to recognize a type of the road for which the signals were recorded. The obtained results might support the identification procedure for the road recognition based on measured signals, especially for vehicles passing from one type of road to another.
Highlights
Cargo securing of trucks and loads is a long-term problem
A the first step, a continuous wavelet transform will be used with possibility of scalograms derivation
This should allow to find specific details related to each fragment of the analysed road surfaces
Summary
Cargo securing of trucks and loads is a long-term problem. According to statistics 25% of accidents involving trucks are caused by inadequate cargo securing in the road transport. Driver or better said driving style is a problem mostly for traffic psychologists All these aspects should be analysed together, including other factors related to e.g. weather or appearance of unexpected conditions. A the first step, a continuous wavelet transform will be used with possibility of scalograms derivation This should allow to find specific details related to each fragment of the analysed road surfaces. Such expectations are based on previous works of the authors, where short-time acoustic signals are analysed by using complex wavelet function type of Gabor [9]. Studying the literature the most common method of identification of road surface roughness as an input to vehicle dynamics is the spectral analysis [13]. The new approach of this paper is to identify the road surface roughness but to study what is happening when passes from on type of the road to another
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