Automated fatigue crack detection for structural health monitoring of metallic aerospace structures

结构健康监测(SHM)提供了在结构的整个使用寿命期间实时监测结构的能力，以确保其安全运行。这种技术有可能在提高安全性的同时显著节省维护和维修成本。出于这个原因，目前航空航天、能源、运输和基础设施部门在SHM技术方面取得了重大的技术进步。声发射(AE)是一种被动健康监测技术，通过检测结构损伤扩展时释放的少量能量，能够对大型结构进行全局实时监测。然而，与许多SHM技术一样，声发射需要操作员对数据进行解释，在复杂结构中可能不太可靠，这被视为工业化实施的最大障碍。由于测量噪声、系统知识的缺乏、操作条件的可变性等造成的不确定性的存在，这一问题变得更加具有挑战性。申请者将在信号处理、多变量统计、新颖性检测和不确定度分析方面发展出色的技能。这项工作的目的是开发数据处理方法，允许自动检测铝吊架的疲劳裂纹。这将包括准确定位损伤、从骨折信号中分离外部噪声、新颖性检测和特征提取的技术。开发的技术将得到广泛的实验疲劳测试计划的支持和验证，申请者将获得声发射监测和实验测试方面的专业知识。所开发的技术还将广泛适用于监测最初的航空航天重点以外的一系列结构。支持文档。

Structural health monitoring (SHM) offers the ability to monitor structures, in real time, throughout their service lives to ensure they are safe for operation. Such technology has the potential to provide significant savings in maintenance and repair costs whilst increasing safety. For this reason there is currently a significant technology pull through for SHM techniques by the aerospace, energy, transport and infrastructure sectors. Acoustic emission (AE) is a passive SHM technique that is able to globally monitor large structures in real-time by detecting small amounts of energy that are released when damage grows in a structure. However, like many SHM techniques acoustic emission requires operator interpretation of data and can be less reliable in complex structures, which is seen as the greatest barrier to industrial implementation. This problem is made all the more challenging by the presence of uncertainty which results from measurement noise, lack of system knowledge, variability in operating conditions, etc. The applicant will develop excellent skills in signal processing, multi-variate statistics, novelty detection and uncertainty analysis. The aim of the work is to develop data processing methodologies that allow the automated detection of fatigue cracking in aluminium hangers. This will include techniques for accurate location of damage, the separation of extraneous noise from fracture signals, novelty detection and feature extraction. The developed techniques will be supported and validated by an extensive experimental fatigue testing programme, where the applicant will gain expertise in acoustic emission monitoring and experimental testing. The developed skills will also be widely applicable to the monitoring of a range of structures outside the initial aerospace focus. Supporting Documentation.