Abstract
In order to improve the prediction ability of welding quality during high-power disk laser welding, a new approach was proposed and applied in the classification of the dynamic features of metal vapor plume. Six features were extracted through the color image processing method. Three features, including the area of plume, number of spatters, and horizontal coordinate of plume centroid, were selected based on the classification accuracy rates and Pearson product-moment correlation coefficients. A support vector machine model was adopted to classify the welding quality status into two categories, good or poor. The results demonstrated that the support vector machine model established according to the selected features had satisfactory prediction and generalization ability. The classification accuracy rate was higher than 90%, and the model could be applied in the prediction of welding quality during high-power disk laser welding.
Highlights
As an important new laser processing technology, high-power disk laser welding has been increasingly widely used in the manufacturing field
During the whole welding process, 2400 images of the welding speed 4.5 m/min were captured by the high-speed camera, and 1480 continuous images from No 521 to 2000 were analyzed
As Feature 4 was added to the feature subset, the accuracy rate increased to 91.55%, especially the accuracy rate of Class E had a sharp increase from 68.65% to 81.92%
Summary
As an important new laser processing technology, high-power disk laser welding has been increasingly widely used in the manufacturing field. Various kinds of sensor methods are applied in the field, such as the use of photodiode signals [1,2,3], spectroscopy [4,5], high-speed photography [6,7,8], acoustic signals [9,10], electrical signals [11], X-rays [12], and so on Among these sensor methods, high-speed photography, which can observe the interaction region between the laser and the workpiece directly, is a kind of non-destructive inspection technique. High-speed photography, which can observe the interaction region between the laser and the workpiece directly, is a kind of non-destructive inspection technique It has become one of the main development trends for online monitoring of the welding process. Pinto-Lopera et al [13] applied a passive vision system using a high-speed camera and an optical filter in real-time measuring of the width and height of weld beads during gas
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