Inter-engine variation analysis for health monitoring of aerospace gas turbine engines

Abstract

This study investigates the development of a new inter-enginevariation analysis method for the purpose of Equipment healthmonitoring, in which the similarity - in both system behaviourand external disturbances - across multiple (sister) engines isleveraged. The sister engine provides a baseline descriptionof the engine under observation, such that the challenge becomesthe differentiation between normal inter-engine variationand the anomalous behaviour, bypassing the need todescribe highly complex engine dynamics. The inter-engineresiduals are modelled directly with input data from both engines,using previous healthy data for training. The trainedmodel is used to compensate known differences between realengines. Anomalous data is detected by comparison of thesimulated output with the true residuals. The method is demonstratedon a real data set containing both nominal, healthy enginedata, and engine data containing anomalies.

Distributed digital twins for health monitoring: resource constrained aero-engine fleet management

“…7), and six flights prior, to the known fault event occurring. These events were not detected by current health monitoring systems, however, compared to the other (assumed correctly functioning) engine on the aircraft, they present the same fault signature [39]. The high magnitude of d for these precursor fault data segments ( d > 100) means they are stored and ranked highly for transmission to ground for further analysis, and thus providing an opportunity to take early action to mitigate the emerging fault.…”