Computer Vision for Inspection of Internal Composite Structure Developed in High-Throughput Manufacturing Processes

用于检查高通量制造工艺中开发的内部复合结构的计算机视觉

• 批准号: RGPIN-2022-05447
• 负责人: Kravchenko, Sergey
• 金额: $ 1.82万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758190
• 关键词: Computer; Vision; Inspection; Internal; Composite

Discontinuous, long fiber-reinforced polymer (DLFRP) composites have gained importance in the transportation industry due to the weight and economic savings they provide. One of the most attractive attributes of DLFRP composites is their ease of manufacturing manufacturability into geometrically complex three-dimensional parts using high-throughput methods such as compression molding. The quality assurance of the fiber orientation distribution (FOD) in a molded part is critical since the configuration of the reinforcing fibers is significantly changed throughout the production process, and the final FOD translates into the part's mechanical and functional properties. Poor production quality control results in significant operational and financial costs as high as 15-20% of annual sales revenue. The current state-of-the-art shows that conventional imagery-based inspection methods for FOD have a number of limitations and the development of advanced inspection methods is instrumental to unlock the full potential that DLFRP composites have to offer for lightweight applications. As such, this NSERC Discovery research program aims at developing a new, integrated multi-physics, multi-scale simulation modeling and experimental approach for FOD analysis in compression-molded DLFRP composites. The main tangible outcomes of this research program will be: (i) technology for online (real-time) data-driven analysis of thermographic imagery for non-destructive inspection of FOD; (ii) enhancement of the fundamental science necessary for technology development; (iii) training highly qualified personnel (HQP) with competencies in manufacturing, inspection, and numerical simulation-based modeling of advanced fiber reinforced polymer composites. Once established and validated, the proposed integrated framework is expected to be widely used by Canadian companies in the aerospace, automotive, and marine sectors, helping them to ensure the quality and repeatability of the mechanical properties in compression-molded DLFRP composite parts. Replacing metal parts with compression-molded DLFRP composites results in up to 40% weight savings which translates to energy savings, fuel economy and reduced global emissions. Compression molding allows mass production of small-to-medium sized, complex-shaped composite parts with zero waste material - these factors play a significant role in reducing the cost and environmental effects of composite manufacturing.

不连续长纤维增强聚合物(DLFRP)复合材料因其重量轻和经济上的节省而在运输行业中获得了重要的地位。DLFRP复合材料最吸引人的特点之一是易于制造，可使用高通量方法(如压缩模塑)制造出几何形状复杂的三维零件。成型零件中纤维取向分布(FOD)的质量保证至关重要，因为增强纤维的结构在整个生产过程中都会发生显著变化，最终的FOD转化为零件的机械和功能性能。糟糕的生产质量控制导致大量的运营和财务成本，高达年销售收入的15%-20%。目前的技术水平表明，传统的基于图像的FOD检测方法具有一定的局限性，先进检测方法的发展有助于释放DLFRP复合材料在轻量化应用中的全部潜力。因此，NSERC Discovery研究计划旨在开发一种新的、集成的多物理、多尺度模拟建模和实验方法，用于压缩模压DLFRP复合材料的FOD分析。这项研究计划的主要有形成果将是：(I)在线(实时)数据驱动的热像分析技术，用于FOD的无损检测；(Ii)加强技术开发所需的基础科学；(Iii)培训具有先进纤维增强聚合物复合材料制造、检验和基于数值模拟的建模能力的高素质人员(HQP)。一旦建立和验证，拟议的集成框架预计将被加拿大航空航天、汽车和海洋行业的公司广泛使用，帮助他们确保压缩模压DLFRP复合材料部件的机械性能的质量和可重复性。用模压DLFRP复合材料替换金属部件可节省高达40%的重量，从而节省能源、燃油经济性和减少全球排放。模压成型能够以零废料批量生产中小型复杂形状的复合材料零件--这些因素在降低复合材料制造的成本和环境影响方面发挥着重要作用。