Implementation of Radial Basis Function Neural Network for Estimation of Strain of Blade

This paper presents estimation of stress and strain of a Rapid prototype product using artificial neural network (ANN). Radial basis function network is used to train the ANN topology. 3D model of blade is developed by using PROE. The model is analyzed using ANSYS to find the Von Mises stress and equivalent strain. The algorithm is trained using 15 values in the input layer of the ANN topology and two values in the output layer: stress and strain that are to be estimated during the testing stage of RBF algorithm.