A Knowledge Mining Method for Green Design Knowledge Driven by Design Information Characteristics

doi:10.3901/JME.2025.09.424

Abstract

Abstract: Currently, due to the huge amount of product design data in the big data and network, the green design knowledge is insufficient for designers, and it is difficulty to effectively green design for the lifecycle of mechanical and electrical products. For above issues, it proposes a knowledge mining method for green design knowledge driven by design information characteristics. Firstly, based on the products’ design procedures, variable types of green information characteristics in design data are analyzed, the identification method of green information is given based on characteristic words recognition. Secondly, considering the requirements of green design for products’ lifecycle, the sequence of green information characteristics is analyzed and set, the expression of green design knowledge is established based on design information characteristics. Then, the relative similarity of green design knowledge characteristics is analyzed, the process of green design knowledge mining driven by design information characteristics is presented, and the evaluation method of green design knowledge is given based on co-occurrence networks. Finally, in design for wind turbines, it analyzes and mines the green design knowledge set with lightweight and other green information characteristics, and the effectiveness of the proposed method is verified in above design application.

Key words: green design knowledge, information characteristics, relative similarity, knowledge mining, life cycle

CLC Number:

TH122

KE Qingdi, LI Zisheng, WANG Ling, CHEN Xiaoxu, ZHANG Lei. A Knowledge Mining Method for Green Design Knowledge Driven by Design Information Characteristics[J]. Journal of Mechanical Engineering, 2025, 61(9): 424-436.

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