Research on Welding Line Defect Recognition of the In-Service Pipeline Using X-Ray Detecting

Abstract

This paper, based on the practical demands of in-service pipeline detection, a set of X-ray digital image welding line defect intelligent recognition system is established. Taking the welding line image detected by X-ray as objects of study, self-adaptive median filter method filters noise, high frequency enhancement filter method conducts the image edge sharpening enhancement; a edge detection method for X-ray digital image based on morphological gradient is proposed; a group of characteristics parameters that accurately reflects the essence characteristic of defects is selected, using a self-organizing, self-adaptive three-layer feed-forward neural network, applying BP algorithm, the BP neural network recognition system is established, thus, to achieve detection and recognition of weld defects.