摘要：As the lifeline of offshore oil and gas production, a submarine pipeline requires regular safety evaluations with proper maintenance according to the evaluation results. At present, the safety factors based on regional-level commonly used factors in engineering are too many, and this leads to conservative evaluation results with a low acceptance of defects. In this paper, a risk factor evaluation index system for submarine pipeline defects is constructed through an analytic hierarchy process (AHP), and the original safety factors are corrected to achieve accurate evaluations for submarine pipeline safety. By constructing a radial basis neural network (RBFNN), the fast calculation of safety factors for other pipeline defects can be realized. Through comparison, it was found that the values obtained by the machine training were in good agreement with the real values, which reflects the accuracy of the model and provides a basis for the repair of a defective pipeline.

关键字：submarine pipeline; safety factor; analytic hierarchy process; radial basis neural network

ISSN号：2071-1050

卷、期、页：卷: 15期: 17

发表日期：2023-09-01

影响因子：0.000000

期刊分区（SCI为中科院分区）：三区

收录情况：SCI（科学引文索引印刷版）,SSCI（社会科学引文索引）,SCIE（科学引文索引网络版）

发表期刊名称：SUSTAINABILITY

参与作者：YASIR MAHMOUD FADUL MUKHTAR

通讯作者：孙伟栋,张家禄

第一作者：左丽丽,董绍华

论文类型：期刊论文

论文概要：孙伟栋,张家禄,YASIR MAHMOUD FADUL MUKHTAR,左丽丽,董绍华，Safety Evaluation Method for Submarine Pipelines Based on a Radial Basis Neural Network，SUSTAINABILITY，2023，卷: 15期: 17

论文题目：Safety Evaluation Method for Submarine Pipelines Based on a Radial Basis Neural Network