Automated ultrasonic inspection of aerospace composites with enhanced defect detection probabilities aided by gantry deployed, CAD controlled robotics (AutoDISC)

在部署的龙门架、CAD 控制机器人 (AutoDISC) 的帮助下，对航空航天复合材料进行自动超声波检测，提高缺陷检测概率

• 批准号: 101800
• 金额: $ 178.37万
• 依托单位: PLANT INTEGRITY LIMITED
• 依托单位国家: 英国
• 项目类别: BEIS-Funded Programmes
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=101800
• 关键词: Automated; ultrasonic; inspection; aerospace; composites

Future generation aircraft will consist mostly of carbon composite materials. The modes of failure in composite intensive aircraft are not fully known as they are still near the beginning of their design life, although it is clear that they are susceptible to internal impact damage, not visible at the surface. Yet current NDI of composites in production and service is still largely manual with low area coverage and NDI images are difficult to interpret for any technique because of macroscopic structural anisotropy. To address these problems the project proposes two key NDI innovations: (1) Up to 100% volume NDI coverage using gantry deployed, CAD controlled robotics so that inspection records at any point can be accurately compared at successive maintenance downtime intervals to allow health diagnostics and progostics. (2) A step increase in current detection probability for composite defects implemented through an inference engine performing similarity analysis on spatial and temporal changes in images with coherent noise removal performed by Bayesian separation. The innovations, validated using ultrasonic NDI, are applicable to any type of NDI sensor.

未来一代飞机将主要由碳复合材料组成。复合材料密集型飞机的失效模式还不完全清楚，因为它们仍处于设计寿命的初期，尽管它们显然容易受到内部冲击破坏，在表面看不到。然而，目前在生产和服务中的复合材料NDI仍然主要是人工进行的，覆盖率低，并且由于宏观结构的各向异性，任何技术都很难解释NDI图像。为了解决这些问题，该项目提出了两项关键的NDI创新：(1)使用部署的门架、CAD控制的机器人实现高达100%的批量NDI覆盖，以便可以在连续的维护停机间隔准确比较任何点的检查记录，以便进行健康诊断和预防。(2)通过推理机对图像的时空变化进行相似性分析，并通过贝叶斯分离进行相干噪声去除，实现了对复合缺陷当前检测概率的逐步增加。这些创新通过超声波无损检测得到验证，适用于任何类型的无损检测传感器。