Cladding pool morphology recognition and closed-loop control method based on instance segmentation

Abstract

The invention discloses a cladding pool morphology recognition and closed-loop control method based on instance segmentation. The cladding pool morphology recognition and closed-loop control method comprises the following steps of initializing arc welding additive manufacturing output power and output power variable quantity; collecting a color image of the arc welding additive manufacturing cladding pool; updating arc welding additive manufacturing output power; segmenting a cladding pool in the cladding pool color image, and meanwhile, generating an instance mask of the cladding pool and pixel coordinates of the candidate frame to complete instance segmentation of the cladding pool; taking the pixel coordinates of the candidate boxes for representing the number of pixels of a long axis and the number of pixels of the fusion width, calculating the variation of the number of pixels of the fusion width, and feeding back the generated output power variation; and judging whether the current cladding pool color image is the last frame or not. The method is good in real-time performance and high in recognition precision, when molten drops cover the edge of the cladding pool, accurate detection and recognition can be achieved, the effectiveness and robustness of the algorithm are verified, the morphology of the cladding pool is detected with low cost and high efficiency, and a reliable basis is provided for real-time evaluation of arc welding additive manufacturing.

Description

technical field [0001] The invention belongs to the technical field of arc welding additive manufacturing and machine vision, and in particular relates to a cladding pool shape recognition and closed-loop control method based on instance segmentation. Background technique [0002] Arc welding additive manufacturing uses the arc as the heat source and the metal welding wire as the material. Based on converting the 3D CAD model of the target into an STL model, the model is layered and sliced ​​according to a certain thickness and direction, and the generated contour is processed. Path planning, complete the filling of materials in a layer-by-layer accumulation manner, and finally generate solid workpieces quickly. In the process of layer-by-layer accumulation, the cladding pool is the smallest forming unit of the target part, and changes in the external environment or process parameters will affect its shape and size, and its fluctuation degree directly affects the forming qua...

AI Technical Summary

Problems solved by technology

[0004] At present, for the analysis and identification of the shape and size of the cladding pool in the process of arc welding and additive manufacturing, some experienced workers can judge whether the printing quality of a single cladding layer is good or bad, but this method requires workers to have rich experience. experience and low efficiency; some use multiple empirical parameters for edge detection, but the validity of the empirical parameters is difficult to verify, and the applicability is low; some use the phase consistency model for edge detection, but the algorithm has a large amount of calculation, Low efficiency, difficult to apply in engineering practice

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