An Investigation into the Capabilities of Artificial Neural Networks(ANN) in Predicting the Location and Depth of Crack on Beam
This paper investigates the capabilities of Artificial Neural Networks (ANN) in predicting the crack location and depth on I-section beam under the clamp boundary condition. Several finite element analyzes have been carried out for the training and testing of the ANN model using MODAL analysis in ANSYS software. The I-section beam is modelled in solid structural beam. The natural frequencies were found through analyzes made using finite element analysis (FEA) software. The ANN model was developed using the algorithm Cascade- forward Back Propagation (CFBP). The validity of the method designed is verified by the determination coefficient (R). It was found that the R 2 (R: coefficient of determination) values are 0.998 for train and test data,
respectively. The result showed that the backpropagation training algorithm was capable of predicting the crack depth and location of solid I-section beam. To evaluate the capability and efficiency of the developed ANN model, the results predicted by ANN are in excellent agreement with the results of the finite element analysis (FEA).This study is useful and contributes significance knowledge to understand the prediction of crack location and depth of I-beam using the ANN model.
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