智辅驱动下的海工船舶感性意象造型优化设计研究

胡浩伟; 胡俊; 秦桂祥

doi:10.19554/j.cnki.1001-3563.2025.20.003

PDF(4716 KB)

包装工程（设计栏目） ›› 2025, Vol. 46 ›› Issue (20) : 25-34. DOI: 10.19554/j.cnki.1001-3563.2025.20.003

工业设计

智辅驱动下的海工船舶感性意象造型优化设计研究

胡浩伟¹, 胡俊^1,*, 秦桂祥²

作者信息 +

Optimization Design of Perceptual Intention Modeling of Offshore Vessels Driven by Intelligent Assistance

HU Haowei¹, HU Jun^1,*, QIN Guixiang²

Author information +

文章历史 +

摘要

目的为补齐我国在海工船舶造型设计领域的局部短板,采用感性工学结合生成式人工智能的设计方法,开发一款符合AHTS船舶感性意象的造型优化设计方案。方法首先通过对海工船舶的类型与功能结构进行分析,确定AHTS船舶的开发优先级;再利用感性工学方法获取海工船舶的典型样本与核心感性意象词汇,并以此结论指导海工船舶造型的AIGC设计开发,组成“感性工学+生成式人工智能”工作流;最后使用云模型的评价方法筛选方案,并深化评分最高的方案。结果以我国某现役8000 HP深水三用工作船为例,获取了最终适用于其的感性意象造型优化方案。结论在理论层面,“感性工学+生成式人工智能”工作流耦合了人类思维与AIGC方法,能够指导海工船舶感性意象造型的设计开发,具备一定先进性与实用价值。在实践层面,海工船舶造型优化方案的提出有利于弥补我国工程船舶造型设计领域的不足,优良的设计方案也能够体现我国船舶制造业的国际影响力,确立我国航海领域“大国重器”的斐然形象。

Abstract

To address partial gaps in the design of offshore vessel modeling in China, the work aims to develop a design optimization scheme aligning with the perceptual image of Anchor Handling Tug Supply vessels with Kansei Engineering and artificial intelligence generated content. The vessel type and functional structure were first analyzed to establish development priorities for AHTS vessels. Core perceptual image vocabulary and representative samples were then obtained through Kansei Engineering, guiding the AIGC-driven design process within an integrated workflow. A cloud model-based evaluation method was applied to screen design alternatives, with the highest-rated scheme selected for further development. With an in-service 8000 HP deep-water platform supply vessel in China as an example, a perceptual image-optimized design scheme was ultimately derived. Theoretically, the integrated workflow couples human cognition with AIGC methods, offering an advanced and practical approach to perceptual image-based design. Practically, the proposed design optimization helps bridge gaps in China's engineering vessel modeling, while high-quality design solutions can enhance the international profile of China's shipbuilding industry and reinforce the image of "critical national assets" in the maritime sector.

导出引用1

胡浩伟, 胡俊, 秦桂祥. 智辅驱动下的海工船舶感性意象造型优化设计研究[J]. 包装工程. 2025, 46(20): 25-34 https://doi.org/10.19554/j.cnki.1001-3563.2025.20.003

HU Haowei, HU Jun, QIN Guixiang. Optimization Design of Perceptual Intention Modeling of Offshore Vessels Driven by Intelligent Assistance[J]. Packaging Engineering. 2025, 46(20): 25-34 https://doi.org/10.19554/j.cnki.1001-3563.2025.20.003

中图分类号： TB472

参考文献

[1] 万里, 吕杰锋, 许晟. 船舶造型设计特性研究与方法探析[J]. 中国舰船研究, 2015, 10(5): 6-15.
WAN L, LYU J F, XU S.Analysis of the Characteristics and Methods of Ship Topside Design[J]. Chinese Journal of Ship Research, 2015, 10(5): 6-15.
[2] 杨延璞, 陈登凯, 成沛瑶. 工业设计决策问题研究[J]. 包装工程, 2020, 41(22): 1-6.
YANG Y P, CHEN D K, CHENG P Y.Decision-Making Problems of Industrial Design[J]. Packaging Engineering, 2020, 41(22): 1-6.
[3] 林丽, 张云鹍. 感性工学中的参数化设计方法关键技术研究现状与展望[J]. 图学学报, 2019, 40(5): 936-944.
LIN L, ZHANG Y K.Key Technologies in Parametric Design Methods in Kansei Engineering: State of Art and Progress[J]. Journal of Graphics, 2019, 40(5): 936-944.
[4] 陈静文, 邢亚龙. 基于感性工学的儿童产品设计方法研究[J]. 机械设计与研究, 2024, 40(4): 261-265.
CHEN J W, XING Y L.Research on Children’s Product Design Methods Based on Kansei Engineering[J]. Machine Design & Research, 2024, 40(4): 261-265.
[5] 杨舒婷, 张学永, 李珍, 等. 基于感性设计方法的战斗机座舱概念设计研究[J]. 包装工程, 2024, 45(4): 33-39.
YANG S T, ZHANG X Y, LI Z, et al.Conceptual Design of Fighter Cockpit Based on Emotional Design Method[J]. Packaging Engineering, 2024, 45(4): 33-39.
[6] 孔德洋, 黄偲蕊, 麻殊捷. 基于情感分析的汽车造型设计感性评价方法[J]. 同济大学学报(自然科学版), 2022, 50(12): 1817-1824.
KONG D Y, HUANG S R, MA S J.Perceptual Evaluation Method of Automobile Styling Design Based on Sentiment Analysis[J]. Journal of Tongji University (Natural Science), 2022, 50(12): 1817-1824.
[7] 王兆杰, 于雷, 熊进辉, 等. 关于AI大模型技术赋能船舶领域的认识[J]. 智能科学与技术学报, 2024, 6(1): 33-40.
WANG Z J, YU L, XIONG J H, et al.Understanding of AI Large Model Technology Empowering the Field of Ships[J]. Chinese Journal of Intelligent Science and Technology, 2024, 6(1): 33-40.
[8] 尹虎, 殷莹熙彤, 陈殿生, 等. 基于AIGC协同工业设计流程的气道廓清辅具设计研究与实践[J]. 包装工程, 2024, 45(16): 51-65.
YIN H, YIN Y, CHEN D S, et al.Research and Practice of Airway Clearance Assistive Device Design Based on AIGC Collaborative Industrial Design Process[J]. Packaging Engineering, 2024, 45(16): 51-65.
[9] 李志, 刘峻江, 肖锦葵. 基于感性工学增强的GPT模型在分布式定制化制造方案中的研究[J]. 工业工程, 2025, 28(3): 16-27.
LI Z, LIU J J, XIAO J K.A GPT Model Enhanced by Kansei Engineering in Distributed Customized Manufacturing Solutions[J]. Industrial Engineering Journal, 2025, 28(3): 16-27.
[10] 王年文, 王劲松, 毕翼飞, 等. 人工智能在感性工学研究中的应用与趋势[J]. 包装工程, 2023, 44(16): 32-40.
WANG N W, WANG J S, BI Y F, et al.Application and Trend of Artificial Intelligence in Kansei Engineering Research[J]. Packaging Engineering, 2023, 44(16): 32-40.
[11] 幸耀庭. 9000 hp深水供应三用工作船结构布置与设计[J]. 船舶标准化工程师, 2024, 57(2): 56-62.
XING Y T.General Arrangement and Structure Design of 9000 Hp Deep-Water Offshore Support Vessel[J]. Ship Standardization Engineer, 2024, 57(2): 56-62.
[12] 罗丽弦, 洪玲. 感性工学设计[M]. 北京: 清华大学出版社, 2015.
LUO L X, HONG L.Kansei Engineering Design[M]. Beijing: Tsinghua University Press, 2015.
[13] 王年文, 王剑. 面向感性需求的家庭服务机器人造型设计研究[J]. 机械设计, 2018, 35(11): 111-116.
WANG N W, WANG J.Modeling Design of Family Service Robot Oriented to Perceptual Demand[J]. Journal of Machine Design, 2018, 35(11): 111-116.
[14] 周俊. 问卷数据分析破解SPSS的六类分析思路[M]. 北京: 电子工业出版社, 2017: 64-120.
ZHOU J.Analysis of Questionnaire Data and Six Kinds of Analysis Ideas of SPSS[M]. Beijing: Publishing House of Electronics Industry, 2017: 64-120.
[15] 高峰, 焦阳. 基于人工智能的辅助创意设计[J]. 装饰, 2019(11): 34-37.
GAO F, JIAO Y.Artificial Intelligence Aided Creative Design[J]. Zhuangshi, 2019(11): 34-37.
[16] 于鹏, 张毅. 从特征辨识到图像生成: 基于AIGC范式的苗族服饰设计[J]. 丝绸, 2024, 61(3): 1-10.
YU P, ZHANG Y.From Feature Recognition to Image Generation: Miao Ethnic Costume Design Based on the AIGC Paradigm[J]. Journal of Silk, 2024, 61(3): 1-10.
[17] 侯云鹏, 彭涵, 刘育晖. 基于LoRA模型的非遗数字化传承: 以楚漆器为例[J]. 设计艺术研究, 2024, 14(1): 14-18.
HOU Y P, PENG H, LIU Y H.Digital Inheritance of Intangible Cultural Heritage Based on the Lo RA Model: A Case Study of Chu Lacquerware[J]. Design Research, 2024, 14(1): 14-18.
[18] ZHANG L,RAO A,AGRAWALA M. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023: 3836-3847.
[19] 何伟军, 曹东杰, 袁亮, 等. 基于组合赋权—云模型的海绵城市韧性水平研究[J]. 生态经济, 2025(5): 1-15.
HE W J, CAO D J, YUAN L, et al.Study on the Resilience Level of Sponge City Based on Combined Weighting-Cloud Model[J]. Ecological Economy, 2024: 2025(5): 1-15.