Prediction of fatigue crack growth rate using rule-based systems

Fatigue crack propagation life has been estimated based on established empirical equations. In the present work, fatigue crack rates of ASTM A533 alloy under the different load histories was predicted by adaptive neuro fuzzy approach (ANFIS). A novel soft-computing application, suitable for non-linear, noisy and complex problems like fatigue. The features and usefulness of our method are to initial the fatigue crack growth rate with the number of cycle's relationship for each case study. In this research, an automatic prediction methodology has been adopted to estimate the constant amplitude loading fatigue life under the above condition by applying neuro fuzzy approach (ANFIS). Soft-computing methods show great potential for predicting the fatigue crack growth rate, especially with really data. The predicted results are found to be in perfect agreement with the experimental findings when tested on ASTM A533 alloy.