Abstract

Working closely with the UK Ministry of Defence (MOD), Smiths has developed a Fleet and Usage Management System (FUMS™) to enable proactive fleet management and continuous diagnostic/prognostic improvements through a single fusion and decision support platform for helicopters, aeroplanes and engines. This paper gives an overview of a suite of FUMS™ algorithms that have been successfully developed for gas turbine applications and validated using a large volume of engine data. The system has been used to analyse both airborne acquired data and ground test-bed data. The system algorithms have been targeted at evaluating the following: stresses of compressor components, thermal transient stresses of turbine components, fatigue. Total Accumulated Cycles (TAC), engine vibration, neural network based performance/degradation and, Usage Indices (UIs) that summarise engine parameters and at the same time indicate the life/condition of engine components. By operating on data from the same engine on two test-beds, the system can be used to normalise the engine vibration and reconcile any differences in vibration-based acceptance/rejection criteria: these differences can result in the acceptance of an engine for on-wing operation at one site and the rejection of the engine at another site. The paper also gives an overview of the FUMS™ intelligent management software, which has allowed the MOD to plug-in 3rd party applications. In this way, MOD can evaluate, verify and procure engine technologies developed by various suppliers and build engine applications from these technologies without the need for software re-writing.

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