Rescaled range analysis of service load data

摘要

Recent advances in data acquisition, storing, and recording technology are allowing increasingly detailed samplings of actual customer usage of product. Because of this, laboratories are coming forward to use the actual road data rather than simulated data or data collected from the proving ground. This research work is an attempt to find a representative length of data (short-term data) from the large-distance data (long-term data). For any particular class of vehicle, finding the short-term data, which are representative of long-term data, will avoid the collection of large-distance data in the future. In this paper, using the Hurst methodology an attempt have been made to find the short-term data that have to be collected, so as to be representative of the long-term data. In this study, data have been collected both on the proving ground as well as on an actual road for a distance of 1700 km on a light commercial vehicle. It has been seen from the Hurst exponent that, collecting data for an actual road length of about 200 km would give a representation for an actual road length of 1000 km.