Research on Product Semantic Features Based On Digital Twin

To solve the problems of low efficiency of aesthetic law acquisition and imperfect design auxiliary function in the process of industrial product innovation design. a product parameter optimization method is constructed to modify the appearance characteristics of the product according to the principle of digital twin and the principle of perceptual engineering. Firstly, the twin database based on product semantic classification is established. With the help of the twin data, the concrete element cluster classification clustering is carried out to obtain the design experience. The obtained semantic element features are reused to optimize the design scheme. The method is applied to a sound product that requires cute semantics. The results prove the feasibility of the method for product appearance optimization, which effectively assist the product appearance design process and optimize the modeling elements.