Jh. Vogel et al., AUTOMATED FATIGUE DATA FITTING USING STRUCTURAL SHIFT DETECTION, Journal of engineering materials and technology, 119(1), 1997, pp. 51-55
A set of data fitting algorithms are presented for determining the cyc
lic material properties used in the local strain approach to fatigue l
ife prediction. These properties are obtained by fitting power-law cur
ves to the elastic and plastic components of uniaxial strain-life fati
gue data obtained under constant amplitude testing. It is well known t
hat these power-law relationships may be expected to be valid only wit
hin a limited range of strain amplitude; it is not uncommon however, t
o have significant amounts of test data outside of this range. The alg
orithms presented here address this problem by applying a structural s
hift detection scheme to the elastic and plastic component life data s
ets to identify the limits of the valid range; The curve fits obtained
are then thefts of only the data lying within this range. The fitting
approach is illustrated for two sets of SAE 1045 steel data. In the e
xamples shown, proper fitting of the curves is seen to improve the qua
lity of life prediction by as much as a factor three.