Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions KU LeuvenAlexandre Miguel Ricardo Mauricio, Konstantinos Gryllias
Perspectives on Health and Usage Monitoring Systems (HUMS) of helicopters KU LeuvenAlexandre Miguel Ricardo Mauricio, Junyu Qi, Konstantinos Gryllias
A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges KU LeuvenKonstantinos Gryllias
Multiple-Model Estimation-based Prognostics for Rotating Machinery KU LeuvenJunyu Qi, Konstantinos Gryllias, Alexandre Miguel Ricardo Mauricio
A Deep Support Vector Data Description Method for Anomaly Detection in Helicopters KU LeuvenChenyu Liu, Konstantinos Gryllias
Using a smartphone camera to analyse rotating and vibrating systems: Feedback on the SURVISHNO 2019 contest KU LeuvenKonstantinos Gryllias, Chenyu Liu, Alexandre Miguel Ricardo Mauricio
Advanced signal processing techniques for helicopter's gearbox monitoring KU LeuvenAlexandre Miguel Ricardo Mauricio, Konstantinos Gryllias
Gear Grinding Monitoring based on Deep Convolutional Neural Networks KU LeuvenChenyu Liu, Alexandre Miguel Ricardo Mauricio, Konstantinos Gryllias
The anomalous and smoothed anomalous envelope spectra for rotating machine fault diagnosis KU LeuvenKonstantinos Gryllias
An informative frequency band identification framework for gearbox fault diagnosis under time-varying operating conditions KU LeuvenKonstantinos Gryllias
