Advanced diagnostics of aircraft structures using automated non-invasive imaging techniques

使用自动化非侵入性成像技术对飞机结构进行高级诊断

• 批准号: 2878991
• 金额: --
• 依托单位: CRANFIELD UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2878991
• 关键词: Advanced; diagnostics; aircraft; structures; using

There is an innovative need for more efficient and reliable damage inspection, reducing time and cost of maintenance without compromising the safety of passengers and goods transported. The ultimate objective of the research is to deliver an automated innovative damage evaluation tool capable to detect and characterize damage on either metallic or composite structures by novel optimised fusion of various advanced imaging technologies such as ultrasound, infrared, visual, etc. The respective scientific results of the research are:1. To provide novel approaches for assessing damage in materials used in the transport sector and identify surface and internal discontinuities with size to depth ratio less than 1.5 and detect the size, type and depth of the defect.2. To develop innovative image recognition methodology capable of fusing the various imaging tools and providing a reliable and automatic detection of different types of defects in metal and composites.3. To develop novel image fusion technology for optimal combination of the developed imaging techniques.4. Software development for the advanced imaging data selection and processing.5. Development of a high precision spatial positioning system, capable of tracking the position of the non-invasive imaging sensors relative to the component under inspection.

在不损害乘客和运输商品的安全的情况下，需要更有效，更可靠的损害检查，减少维护时间和维护成本。这项研究的最终目标是提供一种能够通过新颖的优化各种高级成像技术（例如超声，红外，视觉，视觉，视觉等）进行新的优化融合来检测并表征金属或复合结构的损害的自动创新损害评估工具。研究的各自的科学结果是：1：1。提供新的方法来评估运输部门中使用的材料的损害，并确定尺寸与深度比小于1.5的表面和内部不连续性，并检测缺陷的大小，类型和深度。2。为了开发能够融合各种成像工具的创新图像识别方法，并为金属和复合材料中的不同类型的缺陷提供可靠的自动检测。3。开发新型的图像融合技术，以最佳组合开发成像技术。4。高级成像数据选择和处理的软件开发5。开发高精度的空间定位系统，能够跟踪相对于在检查中的组件相对于组件的非侵入性成像传感器的位置。