An Intelligent Generative Design Method for Peking Opera–Inspired Locomotive Liveries under Cultural and Engineering Constraints

Abstract

Locomotive livery design serves as a vital carrier of cultural identity; however, traditional design workflows exhibit low efficiency, and general AI-generated schemes often lack engineering feasibility due to excessive pattern and color redundancy. This study, taking Peking Opera facial patterns as a representative case, proposes an intelligent generative design method that coordinates cultural expression with engineering constraints. By constructing an element translation strategy based on element complexity, color complexity, and their synergistic "combined matrix" for LoRA-based model training, the results confirm that the combined matrix approach effectively balances cultural identifiability, visual order, and engineering implementability. Verified through expert Fuzzy Comprehensive Evaluation (FCE), this framework provides an efficient methodology for the culture-oriented design of industrial equipment under engineering constraints.

Keywords: Locomotive Livery, Regional Culture, Element Translation, Intelligent Generation

DOI: 10.54941/ahfe1007767