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Enhanced demodulation band selection based on Operational Modal Analysis (OMA) for bearing diagnostics KU Leuven

Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description KU Leuven

Dandan Peng, Chenyu Liu, Wim Desmet, Konstantinos Gryllias

Measurement of the speed of a rotating shaft through smartphone video acquisition exploiting the rolling shutter effect KU Leuven

Toby Verwimp, Alexandre Miguel Ricardo Mauricio, Konstantinos Gryllias

This article investigates the viability of using a smartphone’s rolling shutter camera as a cost-effective tool for rotational speed measurement. The smartphone is pointed to the side of the rotating shaft, on which a zebra pattern is pasted. As a consequence of the rolling shutter effect, the zebra pattern is deformed. This deformation depends on the pose of the shaft with respect to the camera, the intrinsic camera parameters and the ...

Intelligent fault diagnosis of rotating machinery using lightweight network with modified tree-structured parzen estimators KU Leuven

Konstantinos Gryllias

A Siamese hybrid neural network framework for few-shot fault diagnosis of fixed-wing unmanned aerial vehicles KU Leuven

Konstantinos Gryllias

Automatic multi-differential deep learning and its application to machine remaining useful life prediction KU Leuven

Konstantinos Gryllias

A quantitative estimation method of ball bearing localized defect size based on vibration instantaneous energy analysis KU Leuven

Konstantinos Gryllias

Domain Knowledge Informed Unsupervised Fault Detection for Rolling Element Bearings KU Leuven

Douw Marx, Konstantinos Gryllias

Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions KU Leuven

Alexandre Miguel Ricardo Mauricio, Konstantinos Gryllias

Perspectives on Health and Usage Monitoring Systems (HUMS) of helicopters KU Leuven

Alexandre Miguel Ricardo Mauricio, Junyu Qi, Konstantinos Gryllias

Publicaties

Enhanced demodulation band selection based on Operational Modal Analysis (OMA) for bearing diagnostics KU Leuven

Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description KU Leuven

Measurement of the speed of a rotating shaft through smartphone video acquisition exploiting the rolling shutter effect KU Leuven

Intelligent fault diagnosis of rotating machinery using lightweight network with modified tree-structured parzen estimators KU Leuven

A Siamese hybrid neural network framework for few-shot fault diagnosis of fixed-wing unmanned aerial vehicles KU Leuven

Automatic multi-differential deep learning and its application to machine remaining useful life prediction KU Leuven

A quantitative estimation method of ball bearing localized defect size based on vibration instantaneous energy analysis KU Leuven

Domain Knowledge Informed Unsupervised Fault Detection for Rolling Element Bearings KU Leuven

Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions KU Leuven

Perspectives on Health and Usage Monitoring Systems (HUMS) of helicopters KU Leuven