A study on fatigue time series using cross correlation function

Abstract

This paper presents the analysis on variable amplitude (VA) loading strains data using cross correlation function (CCF). CCF is a method to measure a similarity of two fatigue time series as a function of a time-lag applied to one of them. Cross correlation is generally used when measuring information between two different time series. The objective of this study is to observe the capability of this method in detecting the similarity of signal pattern between two critical stress points, a set of case study data consist of nonstationary VA loading strains data that exhibits a random behaviour was used. This random data was collected in the unit of microstrain on the lower suspension arm of a mid-sized sedan car. The data was repetitively measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete data points, travelling on a pave road and highway route. The collected data was then calculated and analysed using CCF. Higher calculated cross correlation coefficient value was then selected to analyse the fatigue analysis for further study.