Industrial, Environmental and Biometric Informatics Laboratory
Università degli Studi di MilanoDepartment of Computer Science
Real-time quality monitoring in laser cutting applications is a key issue in high-tech steel manufacturing industries. We have studied an automated system for intelligent quality analyses that acquires frames related to the temporal evolution of sparks generated by the interaction of the laser with the metal as well as process-related parameters and, on the basis of extracted features, judges the quality of the current cut. It has been demonstrated the existence of a relationship between the shape assumed by the sparks and the quality of the final cut. Based on such relationship, a quality analysis system has been designed, which integrates traditional image processing methods and soft-computing paradigms in order to control the balance between the accuracy of the quality analysis and the computational complexity (related to real-time constraints).
The research have been performed in collaboration with TRUMPF.
Schema of the researched system
Examples of images analyzed by the implemented system