Aircraft health monitoring - towards more electric aircraft

Abstract

iBEARING: The ultimate aim of iBearing is to monitor bearings in real-time, with an embedded sensor, in a harsh environment defined by high speed and vibration, exposure to lubricant, and high temperatures. Moreover, the proposed system will apply an advanced data fusion algorithm to predict remaining useful life time, without operator intervention. This will promote enabling technologies for next generation of high speed, high power aircraft starter-generators, allowing early planning of prompt maintenance or part replacement and suppression of preventive maintenance. The consortium composed by Active Space Technologies, Cranfield University, and The Barden Corporation (UK) Ltd (part of Schaeffler Technologies) have worked with Thales Avionics Electrical Systems to study solutions to achieve the iBearing goal. The selected solutions have been designed, implemented and tested on the Schaeffler test rigs. The future iBearing product will be a miniaturized, integrated device to install in any bearing, requiring minimal adaptations to the shape of new bearings. iGEAR: The ultimate goal of the iGear (Intelligent Gearbox for Endurance Advanced Rotorcraft) project is the development of on-the-fly Structural Health Monitoring (SHM) for gearboxes. This innovative system will be applied to the lateral rotor gearboxes in the framework of the RACER demonstrator for the Fast Rotorcraft IADP. This will promote enabling technologies for next generation gearboxes comprising new composite or ceramic materials. iGear will assess technologies for health monitoring of gearboxes, by enabling early detection of gear and bearing degradation. The ultimate goal is to allow early planning of prompt maintenance or part replacement. This project inherits significant knowledge and developments made by Active Space Technologies and Cranfield University such as the iBearing results, working with partner Avio Aero. The combination of measurements of vibration, acoustic emissions, and lubricant oil will be used for the Lateral Rotor Gearboxes. The key innovation is in the use of data fusion across condition indicators (CIs) to increase the robustness of diagnosis. Traceability is important, linking acceptable rule-based diagnosis based on multiple CIs and probability. iGear will enable embedded system health monitoring in future commercial aircraft.