Monitoring and adaptive control of CO2 laser flame cutting

In this paper a real-time control and optimization system for laser flame cutting of thick plates of mild steel is presented. The proposed system consists of two subsystems, namely a process monitoring and a control and optimization module. The process monitoring module evaluates the cut quality by measuring a set of sensing parameters, which are well-correlated with different quality characteristics of the cut surface. The applicability of different optical sensors (photodiodes and a NIRcamera) has been investigated. An overview of the most suitable set of sensing parameters is presented. The correlations between different quality deteriorations and the sensing parameters are mentioned as well as the reasons for these correlations. The real-time control and optimization module is implemented as an expert system with a dual functionality. On the one hand, it compares the sensing parameters with predefined thresholds and assigns one of the predefined quality classes to the instantaneous cut quality. On the other hand, it modifies the cutting parameters based on the predefined set of interpretable rules corresponding to the identified quality class. The obtained results prove the effectiveness of the chosen approach in terms of increased autonomy, productivity, and efficiency of the process, as well as elimination of the need for manual quality control and the possibility to automatically generate quality reports.