Identification of default from eddy current testing Signals using multi output support vector Machine

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This paper demonstrates the identification of crack size using signals obtained from eddy current testing Signals (ECT). The identification method is based on finite elements with the multi-outputs support vector machines (MO-SVM), The MO-SVM is a statistical learning method that has good generalization capability and learning performance. The finite element method (FEM) is used to create the data set required to train the MO-SVM and the particle swarm optimisation (PSO) is used to find the parameters of MO-SVM. Numerical simulations demonstrate that the MO-SVM method can determine the size of defect with an acceptable accuracy