Toward real-time quality analysis measurement of metal laser cutting

Real-time quality monitoring in laser curling applications is a key issue in high-tech steel manufacturing industries. The paper takes a relevant step in this direction by suggesting an automated system for intelligent quality analyses. The proposed system 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).