基于神经网络优化算法的系泊系统智能设计

doi:10.7623/syxb202505009

石油学报 ›› 2025, Vol. 46 ›› Issue (5): 967-976.DOI: 10.7623/syxb202505009

• 石油工程 • 上一篇

基于神经网络优化算法的系泊系统智能设计

殷启帅^1,2,3, 张来斌^1,2,3, 钟弘成¹, 李博宁⁴, 杨进¹, 马永奇⁵, 闫心业¹, 宋泽华⁶

1. 中国石油大学(北京)安全与海洋工程学院北京 102249;
2. 油气生产安全与应急技术应急管理部重点实验室北京 102249;
3. 国家市场监督管理总局重点实验室(油气生产装备质量检测与健康诊断) 北京 102249;
4. 中国石油大学(北京)石油工程学院北京 102249;
5. 海南大学海洋科学与工程学院海南海口 570228;
6. 中国石油大学(北京)人工智能学院北京 102249

收稿日期:2024-04-28 修回日期:2025-03-10 发布日期:2025-06-10
通讯作者: 殷启帅,男,1991年4月生,2020年获中国石油大学(北京)博士学位,现为中国石油大学(北京)副教授,主要从事海洋油气安全等方面研究工作。Email:yinqs@cup.edu.cn
基金资助:
国家重点研发计划项目(2022YFC2806100)和国家自然科学基金企业创新发展联合基金重点支持项目(No.U22B20126)资助。

Intelligent analysis and design of tensioned mooring system based on backpropagation neural network and genetic algorithm

Yin Qishuai^1,2,3, Zhang Laibin^1,2,3, Zhong Hongcheng¹, Li Boning⁴, Yang Jin¹, Ma Yongqi⁵, Yan Xinye¹, Song Zehua⁶

1. College of Safety and Ocean Engineering, China University of Petroleum, Beijing 102249, China;
2. Key Laboratory of Oil and Gas Safety and Emergency Technology, Ministry of Emergency Management, Beijing 102249, China;
3. Key Laboratory of Oil and Gas Production Equipment Quality Inspection and Health Diagnosis, State Administration for Market Regulation, Beijing 102249, China;
4. College of Petroleum Engineering, China University of Petroleum, Beijing 102249, China;
5. College of Marine Science and Engineering, Hainan University, Hainan Haikou 570228, China;
6. College of Artificial Intelligence, China University of Petroleum, Beijing 102249, China

Received:2024-04-28 Revised:2025-03-10 Published:2025-06-10

摘要/Abstract

摘要： 张紧式系泊系统设计是深水半潜式生产平台总体布置的关键点之一。为研究系泊缆与船体连接点位置、锚点位置和系泊缆构型对系泊缆最大张力与平台最大位移的影响规律,基于数值分析软件建立半潜式平台张紧式系泊系统有限元模型,并通过接入数据接口构建自动仿真程序得到样本集,然后结合反向传播神经网络-遗传算法对系泊系统设计参数进行优化,得到最优的系泊系统参数配置。研究结果表明,通过系泊系统优化前后数据进行对比,系泊缆最大张力减小10.04%,平台最大位移量减小25.29%。该算法所预测误差控制均在10%以内。将数值模拟与神经网络-遗传算法相结合,可为深水半潜式生产平台系泊系统的设计提供工程指导。

关键词: 张紧式系泊系统, 数据接口仿真, 反向传播神经网络, 遗传优化算法, 智能分析设计

Abstract: The design of a tension mooring system plays a key role in the overall layout of deepwater semi-submersible production platforms. To explore the influence of the connection point position between the mooring line and hull, anchor position, and mooring line configuration on the maximum mooring line tension and platform maximum displacement, a finite element model of the tensioned mooring system for semi-submersible platform was established using numerical analysis software in this research. An automatic simulation program was developed through data interface integration to generate a sample set. Subsequently, the backpropagation neural network combined with genetic algorithm was employed to optimize design parameters of the mooring system, thus deriving the optimal mooring system configuration. The results show that compared with the pre-optimization data, the maximum mooring line tension is reduced by 10.04 %, and the platform maximum displacement is reduced by 25.29 % . The prediction error of the algorithm is controlled within 10 % . The combination of numerical simulation with the neural network-genetic algorithm provides engineering guidance for the mooring system design of deep-water semi-submersible production platform.

Key words: tension mooring system, data interface simulation, backpropagation neural network, genetic optimization algorithm, intelligent analysis and design

中图分类号:

TE58

殷启帅, 张来斌, 钟弘成, 李博宁, 杨进, 马永奇, 闫心业, 宋泽华. 基于神经网络优化算法的系泊系统智能设计[J]. 石油学报, 2025, 46(5): 967-976.

Yin Qishuai, Zhang Laibin, Zhong Hongcheng, Li Boning, Yang Jin, Ma Yongqi, Yan Xinye, Song Zehua. Intelligent analysis and design of tensioned mooring system based on backpropagation neural network and genetic algorithm[J]. Acta Petrolei Sinica, 2025, 46(5): 967-976.

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基于神经网络优化算法的系泊系统智能设计

Intelligent analysis and design of tensioned mooring system based on backpropagation neural network and genetic algorithm

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