Quality Monitoring And Control For Laser Cutting With Coaxial Visual Sensing System

Laser cutting is one of the most advanced and important technology for metallic materials processing. Process monitoring and control is significant for high-quality laser cutting. By coaxially detecting the images of the cutting front and the sparks jet, the relationship between the detected signals and cutting quality, including cutting defects (burning or dross) and surface roughness, has been obtained. Self-optimizing control aiming to the best roughness on some certain cutting conditions has been realized.A laminated model of cutting face for evaluating cutting quality has been built up on the basis of cutting experiments. The experimental results and the theoretical analysis of the model show that, the lower part of the cutting face, adjacent to the bottom edge, has the worst cutting quality due to its worst roughness. The quality of the bottom face is mainly depended on the temperature of the lowest part of cutting front. Therefore, the method with this roughness as the main criterion for quality evaluation and detection is reasonable.The vision image of cutting front could not indicate the roughness variation of the bottom edge, but could be used as the criterion identifying cutting defects. The characteristic signal responding to burning occurrence is the jumping standard deviation of both DCF (Distance from Beam Center to Front Edge) and DCB (Distance from Beam Center to Back Edge) of the detected image, while dross occurrence only inducing the jumping standard deviation of DCB.The behavior of sparks has also been investigated by side imaging the sparks jet. It is found that the sparks shapes are related to both the cutting speed and the roughness of the bottom face. On the given condition, the sparks jet length, which corresponds to the pixel quantity of different gray scales, shows an inverted U-curve relationship with the cutting speed. The maximum sparks length occurs at the status of the best roughness of the bottom face, which relates to the optimal cutting speed.Coaxial detecting the sparks jet has also been tried for application to variouscutting directions and attitudes. It is proved that the maximal sparks length of the coaxial image, which can be determined by the highest pixels of different brightness ranges of the sparks image, still corresponds to the best roughness of cutting face. A system for coaxial visual detection and control in laser cutting, as well as the corresponding image processing method has been built up.Experiments for coaxial detecting and optimum controlling of laser cutting quality were performed by simultaneously utilizing the images of both cutting front and sparks jet. The results show that the optimal cutting speed for free defect and the best roughness of the bottom edge could be found automatically and quickly.