Distribution Characterisation of Coil Spring Strain Histories Using Mixed Weibull Analysis - Mahmud, M; Abdullah, S; S. K. Singh, S; K. Ariffin, A; M. Nopiah, Z; Arifin, A (International Journal of Engineering and Technology, 2018)
This paper investigates the scatter of strain histories obtained from coil spring of a vehicle suspension system. Statistical characterisation is essential in fatigue analysis due to the random nature of fatigue process. The element of uncertainty can be dealt with appropriately by applying probabilistic approach. In this study, four different road profiles were used to obtain strain signal data. Initial description of the strain histories was achieved by computing the global statistics values. The strain range data was calculated from the counted fatigue cycle and distribution fitting was performed using the Anderson Darling test. Four different types of distribution; the exponent, Gamma, 3P-Weibull, and 2P-Weibull; were compared to find the appropriate fit to model the strain range data. The results showed that strain range data are highly skewed with thick-tailed indicating a non-Gaussian distribution. All four tested distribution turned out to be insignificance, with the closest p-value of 0.01 produced by the 2P-Weibull distribution at significance level of 0.05. Due to the non-straight probability plot of data, the mixed Weibull distribution was chosen to model the data. The campus area and highway profiles follow this distribution with 2 sub-populations while rural and housing area resulted in 3 sub-populations. Finally, this distribution is found suitable for analysing the strain range data of vehicle coil spring and hence can be used in time-domain fatigue life evaluation.Â Â