Artificial Intelligent Systems and Machine Learning

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


Affiliations
1 Department of Mechanical Engineering, Vinayaka Missions University, Salem, India
2 Department of Mechanical Engineering, PET Engineering College, Tirunelveli District-627117, India
     

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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.

Keywords

Radial Basis Function Network, Finite Element Method, Structural Analysis, and Blade.
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  • Implementation of Radial Basis Function Neural Network for Estimation of Strain of Blade

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Authors

R. I. Rajidap Neshtar
Department of Mechanical Engineering, Vinayaka Missions University, Salem, India
S. Purushothaman
Department of Mechanical Engineering, PET Engineering College, Tirunelveli District-627117, India

Abstract


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.

Keywords


Radial Basis Function Network, Finite Element Method, Structural Analysis, and Blade.