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- W2388442306 abstract "In order to identify the different types of weld defects,the MFL imaging of the weld defect was taken as the research object,a weld defect image recognition method based on GGCM and cluster analysis was worked out.First,three-dimensional MFL signal was converted to a two-dimensional gray-scale image.And then MFL image characteristics of the three weld kinds(weld non-defect,cylinder defects in the weld,rectangular slot defects in the weld) were extracted using GGCM.Also,both clustering algorithms were combined.Characteristic quantities of weld image were selected using the hierarchical clustering method.Then,the characteristic quantities were analyzed using the k-means clustering.And clustering results were showed as visualization graphics.The outcomes indicate that according to the results of cluster analysis of the feature quantities extracted by GGCM,the recognition rate of the typical weld defects is higher than 96%." @default.
- W2388442306 created "2016-06-24" @default.
- W2388442306 creator A5032817042 @default.
- W2388442306 date "2013-01-01" @default.
- W2388442306 modified "2023-09-24" @default.
- W2388442306 title "Clustering Analysis of Weld Defect Based on Gray-gradient Co-occurrence Matrix" @default.
- W2388442306 hasPublicationYear "2013" @default.
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