Abstract
In this study, artificial neural network (ANN) technique is used to predict the friction and wear behavior of various surface-treated structural steel (En 24) fretted against bearing steel (En 31). A three-layer neural network with a back propagation algorithm is used to train the network. Fretting wear volume and coefficient of friction obtained at different normal loads (ranging between 2.4 and 29.4 N) for various treated samples (hardened, thermo-chemically treated, MoS2 coated) were used in the formation of training data of ANN. Results of the predictions of ANN are in good agreement with the experimental results. The degree of accuracy of predictions was 96.3 and 95.7% for fretting friction coefficient and wear, respectively.
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