Using a smartphone camera to analyse rotating and vibrating systems: Feedback on the SURVISHNO 2019 contest KU Leuven
Cyclostationary-based Multiband Envelope Spectra Extraction for bearing diagnostics: The Combined Improved Envelope Spectrum KU Leuven
Combining an optimisation-based frequency band identification method with historical data for novelty detection under time-varying operating conditions KU Leuven
AN IMPROVED 2DCNN WITH FOCAL LOSS FUNCTION FOR BLADE ICING DETECTION OF WIND TURBINES UNDER IMBALANCED SCADA DATA KU Leuven
An increased number of industrial assets are monitored during their daily use, producing large amounts of data. This data allows us to better monitor the health status of these asset, enabling predictive maintenance to reduce risks and costs caused by unexpected machine failure. Many condition monitoring approaches focus on assessing a machine's health status individually. Often, these approaches require historical data sets or handcrafted fault ...