Application of an AIS to the problem of through life health management of remotely piloted aircraft

The operation of RPAS includes a cognitive problem for the operators(Pilots, maintainers, ,managers, and the wider organization) to effectively maintain their situational awareness of the aircraft and predict its health state. This has a large impact on their ability to successfully identify faults and manage systems during operations. To overcome these system deficiencies an asset health management system that integrates more cognitive abilities to aid situational awareness could prove beneficial. This paper outlines an artificial immune system (AIS) approach that could meet these challenges and an experimental method within which to evaluate it

Development of probability of detection data for structural health monitoring damage detection techniques based on acoustic emission

Structural Health Monitoring (SHM) techniques have been developed as a cost effective alternative to currently adopted Non-Destructive Testing (NDT) methods which have well understood levels of performance. Quantitative performance assessment, as used in NDT, needs to be applied to SHM techniques to establish their performance levels as a basis for technique comparison and also as a requirement for practical aerospace application according to set regulations. One such measurand is Probability of Detection (POD). This paper reports experiments conducted to investigate the location accuracy of the Acoustic Emission (AE) system in monitoring events from HsuNielson and fatigue crack AE sources as a route to establish the POD of AE in SHM. It was found that fatigue crack tips could be located at 90% POD within 10 mm accuracy