doiSerbia

Crack sizing by using pulsed eddy current technique and neural Network

Dolapchiev Ivaylo (Technical University of Sofia, Faculty of Electrotechnics, Sofia, Bulgaria)
Brandisky Kostadin (Technical University of Sofia, Faculty of Automation, Sofia, Bulgaria)

A neural network approach for solving an inverse problem of identification of crack width and depth is proposed. Radial Basis Function (RBF) neural networks (NN) perform the identification. It was trained using information from numerical simulated pulsed eddy current (PEC) nondestructive testing (NDT). The capability of the RBF NN was checked with information from numerical and physical experiment. The obtained results illustrate the efficiency of the approach.

Keywords: nondestructive testing, inverse problem, neural networks