H2020 MOIRA ESR1 – Wear monitoring of mechatronic systems under variable operating conditions by integration of heterogeneous data (KU Leuven – WP1）

ESR1 will work on the extraction and exploitation of the hidden information existing in heterogeneous data. Different types of signals, including vibrations, acoustics, wear debris, oil quality and operating conditions will be fused/integrated in order to reveal the relationship between the measured signals and the true degradation of the system, focusing on smart, self-monitored mechatronic systems operating under time-varying conditions. Knowledge and experience from signal processing, tribology, machine dynamics and design, vibrations, acoustics and oil analysis will be combined. ESR1 will work on the underlying physics of the degradation and how this information is present in the captured signals. Wear modelling and tribology tests will be used here. A multi-sensor approach will be employed to capture and analyse the heterogeneous data. Advanced signal-processing tools based on cyclo-stationarity will be developed and applied to the signals, extracting important monitoring indicators. The correlation and quantification of the system degradation with the monitoring indicators will lead to a novel methodology for the prediction of the remaining useful life of mechatronic components. The methodology will be tested and validated on dedicated test rigs, specially designed and constructed at KU Leuven as well as on real industrial signals.