Publications
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Design considerations for smartphone camera-based rotational speed measurement KU Leuven
Condition monitoring of rotating machinery gains importance in order to optimally schedule maintenance and to guarantee operation safety and production efficiency. Varying speed conditions are common in rotating machinery operations, but pose a challenge for vibration analysis. Nevertheless, a direct measurement or an indirect estimation of the rotational speed can simplify the monitoring process. Recent studies have shown that a smartphone's ...
Acoustic Monitoring of Rolling Element Bearings using a Sparse Microphone Array KU Leuven
Acoustic monitoring of rolling element bearings in industrial environments can provide a non-contact solution for early detection of bearing failures and prevention of costly downtime. Nevertheless, extracting the bearing signature of interest from the other contributions in the acoustic signals remains a key challenge. A possible approach to improve the Signal-to-Noise Ratio (SNR) of bearing signatures is to exploit spatial information, ...
A concise self-adapting deep learning network for machine remaining useful life prediction KU Leuven
The influence of the unbalanced magnetic pull on fault-induced rotor eccentricity in induction motors KU Leuven
When performing bearing fault measurements, the unbalanced magnetic pull’s (UMP) influence is inadvertently incorporated. The UMP’s influence distorts the measurements used for bearing fault size estimation, leading to inaccurate fault interpretations. In this paper, we combined a magnetic equivalent circuit motor model with a dynamic bearing model to isolate the UMP’s effect, which is unprecedented in the state of the art. The coupled model is ...