Efficient Intelligent Assembly Modeling Method Based on the Cognition of Interaction Structures

doi:10.3901/JME.2025.12.327

Abstract

Abstract: Focusing on the problem that part models lack the ability of autonomous mating with each other in current assembly modeling methods, a method to endow part models with the cognition ability of interaction structure and realize efficient intelligent assembly modeling is proposed in this paper, combining interaction feature pair (IFP) and BDI (Belief-Desire-Intention) cognition behavior model. A general framework of cognition behavior of part model based on IFP and BDI is proposed, aiming at supporting autonomous search of matching objects and reasoning interaction structures. An automatic construction and association method of compound IFP (C-IFP) is established, which covers both continuous and discrete forms, enhances the description ability of assembly design intent, and forms the belief of part models. Taking advantages of the similarity of the assembly process of similar parts, the part pre-assembly and intelligent assembly algorithms based on C-IFP matching are improved by developing the equivalent matching strategy, with the matching desire of part models being automatically updated, and the matching intention being realized. The results of two case studies show that, compared with strategies considering no similarity, the proposed method improves the efficiency of recognizing the interactive structure of parts and realizing autonomous matching by 97.43%.

Key words: assembly modeling, interaction structure, cognition behavior, agent, high efficiency

CLC Number:

TP301

XIE Junhua, XU Zhijia. Efficient Intelligent Assembly Modeling Method Based on the Cognition of Interaction Structures[J]. Journal of Mechanical Engineering, 2025, 61(12): 327-335,343.

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