Development of Intelligent Defects Detection System

智能缺陷检测系统的开发

• 批准号: 522340-2018
• 负责人: Deiab, Ibrahim
• 金额: $ 1.8万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=648928
• 关键词: Development; Intelligent; Defects; Detection; System

Inspection of products is an integral part of every manufacturing process to ensure that products have the desired quality and**features. Conventionally, the process of inspection usually involves an element of human inspectors; who inspect these products**manually and make sporadic decisions to determine the status of a product, this human inspection is consequentially slow,**reducing productivity and may lead to inconsistency in the quality of inspected parts or products low because of eye fatigue.**Hence, an automatic inspection system becomes an effective way to improve part quality because of the progress of machine**vision technology. Machine vision involves the spontaneous extraction of digital information from processed images or videos for**the purpose of making certain predesigned decisions. . This will involve fundamental research on measurement, quality control,**feature classification and recognition and artificial intelligence as well as applied research, design and development of a test rig**and components selection. The project aims to assist the industry partner efforts to increase efficiency of its operation and quality**of its products.

产品检验是每个生产过程中不可或缺的一部分，以确保产品具有所需的质量和特性。按照惯例，检查过程通常包括人工检查人员；人工检查这些产品**，并做出零星的决定来确定产品的状态，这种人工检查必然是缓慢的，**降低了生产率，并可能导致被检查部件的质量不一致或由于眼睛疲劳而导致产品低。因此，由于机器视觉技术的进步，自动检测系统成为提高零件质量的有效途径。机器视觉涉及从处理过的图像或视频中自发地提取数字信息，以做出某些预先设计的决策。这将涉及测量、质量控制、特征分类和识别、人工智能的基础研究，以及应用研究、试验台的设计和开发以及部件选择。该项目旨在帮助行业合作伙伴努力提高其运营效率和产品质量。