Automatic fuzzy based identification of flawed rivet in Magneto Optic Images

Abstract

Magneto Optic Imaging is a relatively recent Non Destructive Evaluation technique, successfully used to evaluate the integrity of metallic parts in aging aircrafts. In this paper, the authors deal with the implementation of a suitable procedure able to recognize flawed rivets in Magneto Optic measurements. They have been carried out at the NDE Lab, Michigan State University, USA. Exploiting Fuzzy Subtractive Clustering in order to implement the classifier, our proposed approach retrieves a fast and robust applicative, useful for real-time applications. Preliminary results are really encouraging.