Submerged Arc Welding Weld Defect Detection Algorithm Based On Sparse Representation Is Studied

With the development of image processing and pattern recognition technology,computer intelligent evaluation sheet,with its advantages,such as high efficiency,objectivity and economy has been widely applied to oil and gas pipelines in the field of weld defect detection.Since most of weld seam image contain defects,in order to ensure the safe operation of oil and gas pipelines,choose efficient defect detection identification method,is the goal of the people.Therefore,based on the submerged arc welding pipe welding seam X-ray detection images of the object,in view of the possible defects in welding seam area,choose a pattern recognition algorithm of high recognition rate.This article adopts the defect detection of commonly used identification system for the main defects of the weld image type detection and judgment.First of all,through image filtering the results of the analysis type of weld image noise and image after enhancement experiment,selected for weld image enhanced by average filter,Sin,Ostu segmentation,Sobel edge detection and Hough transform of straight by combining image processing system,so as to realize the success of the weld region segmentation.Secondly,by comparing the Ostu and based on density clustering for weld defects and segmentation of image noise,using the latter to split.Again,the use of 6 class characteristic parameters of weld defect and the image noise is described,and the selected characteristic parameters of data analysis and experimental verification.Finally,using support vector machine(SVM)modeling method based on the characteristic parameters so as to realize the recognition of weld defects,got the high recognition rate.In defect recognition system based on support vector machine(SVM)to obtain a higher recognition rate under the premise of extracting characteristic parameters when there is still a calculation error,inevitably affect the result of the identification.In view of this problem,this paper further defect recognition system based on sparse representation,this system according to the weld area is extracted,intercept suspected defect area,sparse representation model is set up the process of implementation of weld defect recognition,effectively avoid the calculation error and has achieved a higher recognition rate.