摘要：Pipelines represent the main mode of transportation for oil and gas, and failure caused by weld defects is the primary cause of accidents, presenting significant risks to personal and environmental safety. Therefore, regularly inspecting pipeline welds is essential for reducing accidents, ensuring personal safety, protecting the environment, and achieving sustainable development. Although manual photographic X-ray inspection is widely utilized for the detection of weld defects in various industries, this process is challenging since X-ray images are noisy and unclear, with uneven grey values. This study proposed a noise reduction framework by introducing a Wiener filter into the wavelet domain to reduce noise in X-ray images while minimizing information loss. Furthermore, a comprehensive evaluation factor that combined contrast and the noise reduction level was proposed to reduce the dependence of image processing performance on wavelet thresholds. Additionally, this study improved the Laplace method by adaptively adjusting the normal and tangential diffusion coefficients to enhance the weld X-ray image contrast without increasing the noise. Through qualitative comparison and quantitative analysis, it has been determined that the suggested methods exhibit better properties than alternative industrial pipeline weld X-ray image processing algorithms. This superiority is observed in objective values as well as subjective visualizations. 漏 Published under licence by IOP Publishing Ltd.

ISSN号：1742-6588

卷、期、页：卷2770期1

发表日期：2024-01-01

期刊分区（SCI为中科院分区）：无

收录情况：EI（工程索引）

发表期刊名称：Journal of Physics: Conference Series

参与作者：刘军,王垚

通讯作者：谢成,刘嘉玥

第一作者：董绍华,徐晴晴

论文类型：会议论文

论文概要：谢成,刘军,王垚,董绍华,徐晴晴,刘嘉玥，Preprocessing method for digital X-Ray weld images，Journal of Physics: Conference Series，2024，卷2770期1

论文题目：Preprocessing method for digital X-Ray weld images