The Design of Reflected Laser Intensity Testing System and Application of Quality Inspection for Laser Cladding Process

Laser cladding is one of the critical technologies for additive manufacturing and rapid repair. Improving cladding performance by materials and process parameters is the leading research direction, but defects and instability of quality in the cladding process are inevitable. Therefore, it is necessary to study which factors are related to quality. In this paper, a new detection method is proposed to measure the radiation intensity of the reflected laser, laser scanning displacement, and temperature of the substrate while cladding. The characteristic values corresponding to the position of the cladding spots are extracted, the cladding quality is preliminarily evaluated and graded, and the correlation between them is verified with the method of machine learning nu-SVM. The results show that the accuracy of the model trained by 300 groups of data to predict the quality grades is 78.74%, which indicates that there is a strong correlation between these process variables and the cladding quality, and this method is feasible for the quality evaluation and control of the cladding process.