Goods and products transported by road are subjected to vehicle vibration which, without proper protective packaging, can suffer damage. To reduce shipment costs, protection has to be optimised to limit product damage occurrence while keeping packaging weight and size to a minimum. Optimisation is realized by simulating the vibration of transport vehicles. To achieve an accurate simulation, each vehicle vibration mode has to be modelled. These include: the nonstationary random vibration induced by road roughness and speed variations, the transient vibration created by road surface aberrations and the harmonic vibration created by the vehicle engine and drive train. Identifying and indexing these mixed-modes within complex road vehicle vibration signals is essential to define the severity and occurrence of the different modes in order to develop an accurate model. This paper shows that indexing can be performed using the orthogonal wavelet transform such as Daubechies 10. Assuming that each mode is preponderant in different analysis scales, the wavelet coefficients can be used to perform the indexing. This allows more sensitive mode detection and a more precise time indexing thanks to the multi-resolution nature of the wavelet transform compared to other time-frequency analysis methods.

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