在飞机气动设计的工程实践中，通常由总体专业提出设计指标，气动设计部门通过多次迭代优化和大量数值模拟计算，逐步实现设计目标，这一过程通常耗费巨大资源。生成式模型展现出直接生成符合预定目标设计方案的潜力，能够显著减少传统设计中的迭代过程。研究中提出了一种基于扩散模型的多目标生成式翼型设计方法，通过将抖振升力系数、巡航阻力系数及厚度等多个性能指标作为条件，生成能够同时满足这些指标的翼型设计方案。采用条件扩散模型来逐步生成设计空间中的有效翼型，避免了传统优化方法中复杂的迭代计算。通过与条件变分自编码器方法的对比试验，展示了扩散模型在生成多样性和条件符合度等方面的优势。结果表明，扩散模型不仅能够生成符合性能要求的翼型，还具备更强的多样性和设计空间探索能力，为未来翼型设计提供了一种高效的新途径。

In the engineering practice of aircraft aerodynamic design， design specifications are typically proposed by the overall engineering team， while the aerodynamic design department implements design goals through numerous iterations and extensive numerical simulations. This process usually consumes significant resources. Generative models show the potential to directly generate design solutions that meet predefined goals， significantly reducing the iterative process in traditional design. This paper proposes a multi-objective generative airfoil design method based on diffusion models. By conditioning on multiple performance metrics such as buffeting lift coefficient， cruise drag coefficient and thickness， the method generates the airfoil designs that simultaneously satisfy these metrics. The use of conditional diffusion models to progressively generate effective airfoils in the design space avoids the complex iterative calculations of traditional optimization methods. Comparative experiments with conditional variational autoencoders demonstrate the advantages of diffusion models in terms of generation accuracy， stability， and diversity. The results indicate that diffusion models can not only generate airfoils that meet performance requirements but also offer greater diversity and design space exploration capability， providing an efficient new approach for future airfoil design.