Fatigue life estimation of an all aluminium alloy 1055 MCM conductor for different mean stresses using an artificial neural network

Abstract

This study is aimed to employ artificial neural networks (ANNs) to predict the fatigue lives of the All Aluminium Alloy Conductor (AAAC) 1055 MCM overhead conductor, considering different values of stretching load (mean stress). For ANN training, three Wöhler (S-N) curves are generated for a conductor/suspension clamp assembly. Twenty-seven fatigue tests are carried out with stretching loads, related to everyday stress (EDS) of 17%, 20% and 25.6% of the conductor’s ultimate tensile strength (UTS), corresponding to mean stresses of 48 MPa, 54 MPa and 73 MPa, respectively. Constant life diagrams (at 105, 106, 107 number of loading cycles) for the AAAC 1055 MCM overhead conductor are built using the ANN. The results confirm that the ANN can accurately predict the fatigue lives of an overhead conductor for various levels of mean stress also when limited experimental data is used for training.