Study on sub-arc X-ray welding image defect segmentation algorithm and defect model

Regarding the present problems that the traditional image segmentation algorithm can only achieve a low successful defect segmentation ratio for the strong noise and low contrast of submerged-arc x-ray image,an efficient X-ray radiography image analysis algorithm is developed for the task of segmentation of submerged-arc welding defects.In the new algorithm,the defect is treated as noise and a new concept-"gray density" is put forward for calculation convenience.Tested with 100 X-ray radiography images obtained from a real factory,the proposed algorithm can increase successful segmentation ratio and achieves a successful ration of 95%.Based on the clustering segmentation algorithm,a high dimension space defect mathematical model is presented.The model makes the characteristic of the complexity of the form into consideration.Real examples show that the model is effective and practical.The sensitivity curve of the presented clustering segmentation algorithm is also given.