面向船舶大型曲面薄板的装配形变TSM-TLHS预测方法

doi:10.16183/j.cnki.jsjtu.2023.576

上海交通大学学报 ›› 2025, Vol. 59 ›› Issue (8): 1092-1102.doi: 10.16183/j.cnki.jsjtu.2023.576

面向船舶大型曲面薄板的装配形变TSM-TLHS预测方法

金轩铖¹, 洪舸¹, 高硕¹, 夏唐斌¹^,²(), 胡小锋¹^,², 奚立峰¹^,²

1.上海交通大学机械与动力工程学院, 上海 200240
2.上海交通大学-弗劳恩霍夫协会智能制造创新中心, 上海 201306

收稿日期:2023-11-14 修回日期:2023-12-29 接受日期:2024-01-12 出版日期:2025-08-28 发布日期:2025-08-26
通讯作者: 夏唐斌 E-mail:xtbxtb@sjtu.edu.cn
作者简介:金轩铖(1999—),硕士生,从事船舶分段装配的质量控制研究.
基金资助:
国家重点研发计划重点项目(2022YFF0605700);上海交通大学深蓝计划基金(SL2021MS008);中船-交大海洋装备前瞻创新联合基金面上项目(22B010432)

TSM-TLHS Prediction Method for Assembly Deformation of Large Curved Thin Plates in Shipbuilding

JIN Xuancheng¹, HONG Ge¹, GAO Shuo¹, XIA Tangbin¹^,²(), HU Xiaofeng¹^,², XI Lifeng¹^,²

1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2. Fraunhofer Project Center for Smart Manufacturing at Shanghai Jiao Tong University, Shanghai 201306, China

Received:2023-11-14 Revised:2023-12-29 Accepted:2024-01-12 Online:2025-08-28 Published:2025-08-26
Contact: XIA Tangbin E-mail:xtbxtb@sjtu.edu.cn

摘要/Abstract

摘要：

船舶分段装配过程中,大型曲面薄板(如外板)放置在胎架上时,会受重力作用发生形变,将影响装配精度进而影响分段建造质量.为预测给定胎架布局下大型曲面薄板的形变,建立了一种基于两阶段拉丁超立方采样和Transformer神经网络结构的代理模型(TSM-TLHS).首先,设计了两阶段拉丁超立方采样,相较传统方法,能直接适用于形状不规则薄板的采样.同时,建立了包含多头注意力模块和位置编码的Transformer代理模型,综合考虑了胎架位置与胎架布置点位移对薄板形变的影响.实际案例结果显示,提出的TSM-TLHS方法的预测误差仅为61 μm,且满足现场装配对薄板形变的预测精度需求,便于船厂及时对分段进行反变形补偿,从而确保装配质量.

关键词: 分段装配, 曲面薄板, 形变预测, 代理模型, 拉丁超立方采样

Abstract:

During the block assembly, large curved thin plates (such as outer plates) undergo deformation due to the force of gravity when they are placed on the jigs, which affects the accuracy and quality of the block assembly in shipbuilding. In order to predict the deformation of these large curved thin plates within a given jig layout, this paper introduces a Transformer-based surrogate model with two-stage Latin hypercube sampling (TSM-TLHS). Primarily, compared to traditional approaches, the two-stage Latin hypercube sampling (TLHS) method enables direct sampling of irregularly shaped thin plates. Simultaneously, this paper uses a Transformer-based surrogate model (TSM) incorporating multi-head attention modules and positional encoding to comprehensively consider the impact of jig positions and corresponding node displacements on thin plate deformation. Real case results demonstrate that the prediction error of this TSM-TLHS method is only 61 μm, meeting the on-site assembly precision requirements for predicting plate deformation. This facilitates timely anti-deformation compensation by block in shipyards, ensuring assembly quality.

Key words: block assembly, curved thin plates, deformation prediction, surrogate model, Latin hypercube sampling

中图分类号:

TH183

金轩铖, 洪舸, 高硕, 夏唐斌, 胡小锋, 奚立峰. 面向船舶大型曲面薄板的装配形变TSM-TLHS预测方法[J]. 上海交通大学学报, 2025, 59(8): 1092-1102.

JIN Xuancheng, HONG Ge, GAO Shuo, XIA Tangbin, HU Xiaofeng, XI Lifeng. TSM-TLHS Prediction Method for Assembly Deformation of Large Curved Thin Plates in Shipbuilding[J]. Journal of Shanghai Jiao Tong University, 2025, 59(8): 1092-1102.

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参数名称	数值
编码器	4
heads	16
channels	80
学习率	0.001(40 epoch之前);0.000 01(40 epoch之后)
epoch	100
训练批量	20

运算名称	T/s
模型训练	3 600
模型预测	0.03
FEA方法计算	480

层数	类型	输出通道数
1-1	全连接层	180
1-2	ReLU	180
2-1	全连接层	160
2-2	ReLU	160
3	全连接层	1

方法	平均形变/mm	M/mm	平均输出误差/%
TSM-TLHS	10.61	0.08	0.7
实际案例结果	10.69	0.08	0.7

面向船舶大型曲面薄板的装配形变TSM-TLHS预测方法

TSM-TLHS Prediction Method for Assembly Deformation of Large Curved Thin Plates in Shipbuilding

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