Molten pool image processing and quality monitoring of laser cladding process based on coaxial vision

Abstract

Aiming at the problems of the traditional detection method of cladding quality in laser cladding process, which relies on experience, has low accuracy and long recognition time, a method based on the image area of molten pool is proposed to detect cladding quality. Firstly, the median filter algorithm with dynamic adjustment of filter window is used to reduce noise and the iterative threshold segmentation algorithm is used to separate the molten pool from the boundary, then the edge of the molten pool is extracted by Canny algorithm which can adaptively change the high and low thresholds and finally the area value of the molten pool is obtained according to the correspondence between the pixel value and the actual value. The relationship between three key factors (nozzle angle, scanning speed and laser power) and molten pool area is analyzed to achieve favorable cladding quality. The results show that the influence of nozzle angle on the molten pool area is anisotropic. And the molten pool area decreases monotonically with the increase of scanning speed, while the higher velocity will destroy the formation of the molten pool. In addition, with the increase of laser power, the expansion of molten pool area is intensified. At the same time, the analysis of the change of molten pool area over time can quickly and accurately detect the three defects (protrusion, depression, and slag inclusion) in the process of cladding.