Random Fatigue Load History Reconstruction

A concise method for modeling nonstationary fatigue loading histories is presented. The mininum number of model parameters is achieved by fitting the variations in mean and variance by a truncated Fourier series. An autoregressive moving average (ARMA) model is used to describe the stationary component. Justification of the method is made by comparing fatigue relevant parameters obtained when subjected to the original and reconstructed histories. In spite of a relatively small number of parameters required, the model is shown to give good results that fall within the bounds predicted by the orginal history.