摘要：Defect recognition and assessment are essential technologies for the safety of pipelines. Recently, deep neural network methods have shown great progress in recognizing pipeline weld defects. However, the current methods cannot achieve online quality assessment for overall girth welds. To solve this problem, this paper proposes a novel quality assessment algorithm for defect recognition and assessment of X-ray girth weld images. First, a two-stage defect classifier based on residual neural network (ResNet) is proposed, which consists of a ResNet18 region classifier and a ResNet50 defect classifier. It can make up for the lack of a single classifier so that the performance and speed of defect recognition can be improved. Second, the feature-extraction calculator is used to extract and calculate the area of the weld defects based on the smallest bounding rectangle method. Third, we propose a quality evaluator based on an improved ensemble learning algorithm and long short-term memory (LSTM), so that the girth welds can be well assessed. Finally, an experiment is conducted using pipeline girth weld X-ray images. The analytic hierarchy process (AHP) method is used to comprehensively assess the level of overall girth-weld defects. The experimental results show that the proposed method is effective in recognizing and evaluating the girth-weld defects of X-ray images. And the accuracy of the quality evaluator can reach 92% for the quality assessment of overall girth welds, compared with manual quality decisions. It effectively achieves online quality assessment for girth welds and has higher evaluation accuracy.

关键字：Girth-weld defects recognition; X-ray images; Improved ensemble learning algorithm; Deep neural network; Quality assessment

ISSN号：1949-1190

卷、期、页：卷: 14期: 1

发表日期：2023-02-01

影响因子：0.000000

期刊分区（SCI为中科院分区）：四区

收录情况：SCI（科学引文索引印刷版）,SCIE（科学引文索引网络版）

发表期刊名称：JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE

参与作者：吴婷婷

通讯作者：高博轩,苗兴园

第一作者：赵弘

论文类型：期刊论文

论文概要：高博轩,赵弘,苗兴园,吴婷婷，Quality Assessment Algorithm of X-Ray Images in Overall Girth Welds Based on Deep Neural Network，JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE，2023，卷: 14期: 1

论文题目：Quality Assessment Algorithm of X-Ray Images in Overall Girth Welds Based on Deep Neural Network