Multi-criteria decision-making method-based approach to determine a proper level for extrapolation of Rainflow matrix

Abstract

To obtain the genuine load spectra of the components of engineering vehicles, the influencing factors in the extrapolation of load spectra should be considered because these are of paramount importance. In the present paper, a multi-criteria decision-making method (MCDM) is proposed to determine the proper upcrossing of the high and low levels (UHLL) for extrapolation of the Rainflow matrix (RFM). First, the distribution characteristics of load amplitude extracted from observed RFMs are obtained. Subsequently, five criteria, namely, the statistic of mean, statistic of variance, coefficient of skewness, coefficient of kurtosis, and the experts’ preference, are selected to describe the fitting accuracy of the Weibull probability density function. Finally, the relationship between the load threshold and the level crossing function is determined after calculating their relative importance, and consequently, the proper UHLL is obtained. The usefulness and validity of the proposed method is illustrated by two typical load-time histories. Results show that the MCDM-based method can combine the subjective and objective factors and obtain an optimal load level.