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.

在不损害乘客和货物安全的情况下，需要进行更有效和可靠的损坏检查，减少维修时间和成本。该研究的最终目标是提供一种自动化的创新损伤评估工具，能够通过各种先进成像技术（如超声、红外、视觉等）的新型优化融合，检测和表征金属或复合结构的损伤。研究的科学成果分别是：1。提供新的方法来评估运输部门使用的材料的损伤，识别尺寸与深度比小于1.5的表面和内部不连续性，并检测缺陷的尺寸，类型和深度。开发创新的图像识别方法，融合各种成像工具，为金属和复合材料中不同类型的缺陷提供可靠和自动的检测。开发新的图像融合技术，实现现有成像技术的最佳组合。先进成像数据选择与处理软件开发。开发高精度空间定位系统，能够跟踪非侵入式成像传感器相对于被检查部件的位置。