Automated Integrity Assessment of Self-Piercing Rivet Joints: i4.0 Approach

自冲铆钉接头的自动完整性评估：i4.0 方法

• 批准号: LP190100165
• 负责人: Prof Alireza Bab-Hadiashar
• 金额: $ 19.95万
• 依托单位: RMIT University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-09-02 至 2023-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP190100165
• 关键词: Automated; Integrity; Assessment; Self; Piercing

Lightweighting in the car industry by the use of aluminium reduces emissions substantially. It entails joining the car body sections by self-piercing rivets rather than the traditional spot welds. We aim to fill the technology gap for effective quality control of these joints. The project expects to solve the problem by merging industry 4.0 principles, three-dimensional X-ray technology, machine learning computer vision and structural mechanics. The expected outcomes are technologies for automation-friendly assessment of these joints. This should benefit industries from medical to electronics to automatically spot a random and delicate abnormality within a solid of complex geometry, such as that in live tissue or an electronic circuit.

通过使用铝来实现汽车工业的轻量化可大大减少排放。它需要通过自冲铆钉而不是传统的点焊来连接车身部分。我们的目标是填补这些接头有效质量控制的技术空白。该项目期望通过融合工业4.0原理、三维X射线技术、机器学习计算机视觉和结构力学来解决该问题。预期成果是对这些关节进行自动化友好评估的技术。这应该有利于从医疗到电子等行业，以自动发现复杂几何形状的实体（例如活体组织或电子电路中的异常）中的随机且微妙的异常。