人机混合交互的产品设计知识图谱构建及智能推理方法

doi:10.3901/JME.2025.03.142

摘要/Abstract

摘要： 产品设计是面向用户需求的反复迭代并逐步进化的创造性活动，其核心是多领域知识应用。为了解决产品设计中知识可视化程度低、人机交互下知识推理弱等问题，提高产品设计智能化程度，提出了基于知识图谱(Knowledge graph, KG)技术的产品交互式设计知识应用模型。首先，基于产品设计活动间的作用与交互演进机制，分析产品设计问题与求解知识间的关联关系，构建一种可扩展的多层产品设计知识图谱(An expandable multi-layer knowledge graph for product design, m-KGPD)用以结构化组织多领域、跨学科求解知识，建立知识需求-求解知识信息检索通道。其次，利用数据标注平台doccano开展知识文本标注和模型训练集构建并基于双向编码表征模型-双向长短时记忆网络-条件随机场(BERT-BiLSTM-CRF)模型开展求解知识实体关系抽取，减轻在大规模文本知识提取工作中的人工重复性操作，利用知识图谱可视化平台GraphXR完成图谱搭建。最后，基于交互式遗传算法(Interactive genetic algorithm，IGA)提出满足产品交互式设计演进规律的求解知识集迭代化推理方法，通过人机混合交互方式为产品设计知识需求匹配最优求解知识集。以复杂地形多岩层成孔装备交互设计过程为例，验证了方法的可行性与有效性。

关键词: 产品设计, 知识图谱, 交互式遗传算法, 知识推理

Abstract: Product design is a creative activity oriented to the iterative and progressive evolution of user requirements, which centers on the application of multi-domain knowledge. To address the problems of low knowledge visualization in product design, weak knowledge reasoning under human-computer interaction and to improve the degree of product design intelligence, a product interactive design knowledge application model based on knowledge graph (KG) is proposed. Firstly, based on the role and interaction evolution mechanism between product design activities, the correlations between product design problems and solution knowledge are analyzed, and an expandable multi-layer knowledge graph for product design (m-KGPD) is constructed and used to structurally organize cross-domain, multi-disciplinary solution knowledge and to establish a knowledge requirement-solution knowledge information retrieval channel. Secondly, the data annotation platform doccano is used to carry out knowledge text annotation and model training set construction, and based on the BERT-BiLSTM-CRF model to carry out solution knowledge entity relationship extraction, to alleviate the repetitive manual operations in the large-scale textual knowledge extraction. The knowledge graph visualization platform GraphXR is used to complete the graph construction. Finally, based on the interactive genetic algorithm (IGA), an iterative inference method is proposed to satisfy the evolution rule of interactive product design, and match the optimal solution knowledge set for the product design knowledge requirements through the hybrid human-computer interaction. The feasibility and effectiveness of the method are verified by taking the interaction design process of the complex multi-rock formation hole-forming equipment as an example.

Key words: product design, knowledge graph, interactive genetic algorithm, knowledge reasoning

中图分类号:

TG156

郭鑫, 黄泽川, 王杰, 张凯, 赵武. 人机混合交互的产品设计知识图谱构建及智能推理方法[J]. 机械工程学报, 2025, 61(3): 142-153.

GUO Xin, HUANG Zechuan, WANG Jie, ZHANG Kai, ZHAO Wu. Knowledge Graph Construction and Intelligent Reasoning Methods for Human-computer Hybrid Interaction in Product Design[J]. Journal of Mechanical Engineering, 2025, 61(3): 142-153.

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