Abstract:

Due to the large number of helicopter components and the complex constraint relationships between them, traditional assembly sequence planning methods encounter the problems of exponential explosion and local optimal solution. To address the difficulties posed by the exponential increase of running time with the number of components and complex calculations of multi-constraint relationship matrix, knowledge graphs (KG) were introduced to establish intuitive semantic assembly information models. A KG -based method for planning the assembly sequence of helicopter components was proposed. Firstly, key assembly information such as structure information and constraint relationships was extracted based on 3D model analysis and knowledge reasoning. Secondly, an assembly information model in the form of KG was constructed based on ontology. Finally, a graph planning algorithm with feedback was employed to determine the assembly sequence of helicopter components from the KG. The priority relationships provided in the KG reduced the search space of the algorithm. Under the constraint of these priority relationships, the graph planning algorithm with feedback aimed to minimize the number of assembly direction changes and the number of assembly tool changes. It gradually planned the sequence, and fed back the planning results to avoid repeated searches. The middle piece of the helicopter mid-fuselage was used as an experimental object to verify the effectiveness of the proposed method. The proposed method achieved higher fitness for the assembly sequence and shorter solution times compared to heuristic algorithms.

Key words: knowledge graph, helicopter component, assembly sequence planning, semantic information model, graph algorithm, 3D model analysis