Restoring damaged components is a very promising and high-value project, which enable to save a lot of production time and cost, and thus has already attracted wide attention, especially in the aviation industry. In the past few years, cold spray (CS) had been widely adopted in restoration and repair applications due to its unique advantages, such as no thermal influence, high efficiency, flexibility, etc. Nowadays, speeding up the product lifecycle as well as improving the accuracy and reliability of CS based repairing require an advance strategy with higher efficiency and more agility. To respond to this need, in this article, a concept on the development of a knowledge based intelligent CS repairing framework is presented. The framework includes a 3D scanning system for providing the information needed on the partially damaged part to repair, a dynamic defect repairing knowledge base for providing related standard defect geometry repairing strategy, including matching the standardized defect geometry, machining pre-treatment, CS toolpath, CS parameter setting, etc., and a CS additive repair system involving robotic repair trajectory programming, simulation and material deposition. Based on the proposed framework, the design of intelligent CS additive repair system and its flow are explained. The novel repair strategy and method proposed in this article can become a model for the metal repair industry in the future.

恢复损坏的组件是一个非常有前途的高价值项目，它可以节省大量的生产时间和成本，因此已经引起了广泛的关注，尤其是在航空业。在过去的几年中，冷喷涂（CS）由于其无热影响，高效，灵活等独特优势而被广泛用于修复和修复应用中。如今，加快产品生命周期并改善产品质量基于CS的维修的准确性和可靠性要求具有更高效率和更高敏捷性的先进策略。为了满足这种需求，在本文中，提出了有关开发基于知识的智能CS修复框架的概念。该框架包括一个3D扫描系统，用于提供部分损坏的零件上需要修复的信息，一个动态缺陷修复知识库，用于提供相关的标准缺陷几何修复策略，包括匹配标准化缺陷几何，加工预处理，CS刀具路径，CS参数设置等；以及一个涉及机器人修复轨迹编程，模拟的CS附加修复系统和材料沉积。在此框架的基础上，对智能型CS添加剂修复系统的设计及其流程进行了说明。本文提出的新颖的维修策略和方法可以成为未来金属维修行业的典范。以及CS附加修复系统，涉及机器人修复轨迹编程，模拟和材料沉积。在此框架的基础上，对智能型CS添加剂修复系统的设计及其流程进行了说明。本文提出的新颖的维修策略和方法可以成为未来金属维修行业的典范。以及CS附加修复系统，涉及机器人修复轨迹编程，模拟和材料沉积。在此框架的基础上，对智能型CS添加剂修复系统的设计及其流程进行了说明。本文提出的新颖的维修策略和方法可以成为未来金属维修行业的典范。