Flaws Identification Using an Approximation Function and Artificial Neural Networks

This paper presents flaws identification algorithm using artificial neural networks and an approximation function. An eddy current differential transducer was used to detect artificial flaws in thin conducting plates. The measured signals were approximated and utilized for flaws identification. Various experiments with rectangular and complex flaws were carried out in order to verify usability of the proposed technique