Classification of plume and spatter images was studied to evaluate the welding stability. A high-speed camera was used to capture the instantaneous images of plume and spatters during high power disk laser welding. Ch...Classification of plume and spatter images was studied to evaluate the welding stability. A high-speed camera was used to capture the instantaneous images of plume and spatters during high power disk laser welding. Characteristic parameters such as the area and number of spatters, the average grayscale of a spatter image, the entropy of a spatter grayscale image, the coordinate ratio of the plume centroid and the welding point, the polar coordinates of the plume centroid were defined and extracted. Karhunen-Loeve transform method was used to change the seven characteristics into three primary characteristics to reduce the dimensions. Also, K-nearest neighbor method was used to classify the plume and spatter images into two categories such as good and poor welding quality. The results show that plume and spatter have a close relationship with the welding stability, and two categories could be recognized effectively using K-nearest neighbor method based on Karhunen-Loeve transform.展开更多
High-speed photography was used to obtain the dynamic changes in the surface plasma during a high-power disk laser welding process. A color space clustering algorithm to extract the edge information of the surface pla...High-speed photography was used to obtain the dynamic changes in the surface plasma during a high-power disk laser welding process. A color space clustering algorithm to extract the edge information of the surface plasma region was developed in order to improve the accuracy of image processing. With a comparative analysis of the plasma features, i.e., area and height, and the characteristics of the welded seam, the relationship between the surface plasma and the stability of the laser welding process was characterized, which provides a basic understanding for the real-time monitoring of laser welding.展开更多
During high power disk laser welding, the high-speed photography was used to measure the dynamic images of the laser-induced plume at different laser welding speeds. Various plume features （area, height and brightnes...During high power disk laser welding, the high-speed photography was used to measure the dynamic images of the laser-induced plume at different laser welding speeds. Various plume features （area, height and brightness） were extracted from the images by the color space clustering algorithm. Combined with observation on the surface and the cross sections of welding samples, the effect of welding speed on welding stability was analyzed. From the experimental results, it was found that these features of plume could reflect the welding state. Thus changes of the plume features corresponded to different welding speeds, which was helpful for monitoring the laser welding stability.展开更多
During deep penetration laser welding,there exist plume（weak plasma） and spatters,which are the results of weld material ejection due to strong laser heating.The characteristics of plume and spatters are related to ...During deep penetration laser welding,there exist plume（weak plasma） and spatters,which are the results of weld material ejection due to strong laser heating.The characteristics of plume and spatters are related to welding stability and quality.Characteristics of metallic plume and spatters were investigated during high-power disk laser bead-on-plate welding of Type 304 austenitic stainless steel plates at a continuous wave laser power of 10 kW.An ultraviolet and visible sensitive high-speed camera was used to capture the metallic plume and spatter images.Plume area,laser beam path through the plume,swing angle,distance between laser beam focus and plume image centroid,abscissa of plume centroid and spatter numbers are defined as eigenvalues,and the weld bead width was used as a characteristic parameter that reflected welding stability.Welding status was distinguished by SVM（support vector machine） after data normalization and characteristic analysis.Also,PCA（principal components analysis） feature extraction was used to reduce the dimensions of feature space,and PSO（particle swarm optimization） was used to optimize the parameters of SVM.Finally a classification model based on SVM was established to estimate the weld bead width and welding stability.Experimental results show that the established algorithm based on SVM could effectively distinguish the variation of weld bead width,thus providing an experimental example of monitoring high-power disk laser welding quality.展开更多
基金Project (51175095) supported by the National Natural Science Foundation of ChinaProjects (10251009001000001,9151009001000020) supported by the Natural Science Foundation of Guangdong Province,ChinaProject (20104420110001) supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘Classification of plume and spatter images was studied to evaluate the welding stability. A high-speed camera was used to capture the instantaneous images of plume and spatters during high power disk laser welding. Characteristic parameters such as the area and number of spatters, the average grayscale of a spatter image, the entropy of a spatter grayscale image, the coordinate ratio of the plume centroid and the welding point, the polar coordinates of the plume centroid were defined and extracted. Karhunen-Loeve transform method was used to change the seven characteristics into three primary characteristics to reduce the dimensions. Also, K-nearest neighbor method was used to classify the plume and spatter images into two categories such as good and poor welding quality. The results show that plume and spatter have a close relationship with the welding stability, and two categories could be recognized effectively using K-nearest neighbor method based on Karhunen-Loeve transform.
基金supported in part by National Natural Science Foundation of China (No.51175095)the Guangdong Provincial Natural Science Foundation of China (10251009001000001, 9151009001000020, 07001764)the Specialized Research Fund for the Doctoral Program of Higher Education of China (20104420110001)
文摘High-speed photography was used to obtain the dynamic changes in the surface plasma during a high-power disk laser welding process. A color space clustering algorithm to extract the edge information of the surface plasma region was developed in order to improve the accuracy of image processing. With a comparative analysis of the plasma features, i.e., area and height, and the characteristics of the welded seam, the relationship between the surface plasma and the stability of the laser welding process was characterized, which provides a basic understanding for the real-time monitoring of laser welding.
基金supported by National Natural Science Foundation of China(No.51175095)the Guangdong Provincial Natural Science Foundation of China(Nos.10251009001000001,9151009001000020)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20104420110001)
文摘During high power disk laser welding, the high-speed photography was used to measure the dynamic images of the laser-induced plume at different laser welding speeds. Various plume features （area, height and brightness） were extracted from the images by the color space clustering algorithm. Combined with observation on the surface and the cross sections of welding samples, the effect of welding speed on welding stability was analyzed. From the experimental results, it was found that these features of plume could reflect the welding state. Thus changes of the plume features corresponded to different welding speeds, which was helpful for monitoring the laser welding stability.
基金partly supported by National Natural Science Foundation of China(No.51175095)Guangdong Provincial Natural Science Foundation of China(No.10251009001000001)the Guangdong Provincial Project of Science and Technology Innovation of Discipline Construction,China(No.2013KJCX0063)
文摘During deep penetration laser welding,there exist plume（weak plasma） and spatters,which are the results of weld material ejection due to strong laser heating.The characteristics of plume and spatters are related to welding stability and quality.Characteristics of metallic plume and spatters were investigated during high-power disk laser bead-on-plate welding of Type 304 austenitic stainless steel plates at a continuous wave laser power of 10 kW.An ultraviolet and visible sensitive high-speed camera was used to capture the metallic plume and spatter images.Plume area,laser beam path through the plume,swing angle,distance between laser beam focus and plume image centroid,abscissa of plume centroid and spatter numbers are defined as eigenvalues,and the weld bead width was used as a characteristic parameter that reflected welding stability.Welding status was distinguished by SVM（support vector machine） after data normalization and characteristic analysis.Also,PCA（principal components analysis） feature extraction was used to reduce the dimensions of feature space,and PSO（particle swarm optimization） was used to optimize the parameters of SVM.Finally a classification model based on SVM was established to estimate the weld bead width and welding stability.Experimental results show that the established algorithm based on SVM could effectively distinguish the variation of weld bead width,thus providing an experimental example of monitoring high-power disk laser welding quality.
