Artificial intelligent modeling to predict tensile strength of inertia friction-welded pipe joints

Abstract

Adaptive neural network-based fuzzy inference system (ANFIS) is an artificial intelligent neuro-fuzzy technique used for modeling and control of ill-defined and uncertain systems. The present paper proposes this novel technique of ANFIS to predict the tensile strength of inertia friction-welded tubular pipe joints with the aid of artificial neural network approach combined with the principle of fuzzy logic. The proposed model is multiple input–single output type of model which uses rotational speed and forge load as input signals. The set of rules has been generated directly from the experimental data using ANFIS. The performance of the proposed model is validated by comparing the predicted results with the actual practical results obtained by conducting the confirmation experiments. The application of χ 2 test confirms that the values of tensile strength predicted by proposed ANFIS model are well in agreement with the experimental values at 0.1 % level of significance. The proposed model can also be used as intelligent online adaptive control model for pipeline welding.