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Abstract
This study attempts to improve the performance of Generalized Likelihood Ratio Test-based indicators via
blind filtering the of vibration signals. The key point is the optimization of the filter coefficients to maximize
the indicator of interest. The filter coefficients are optimized through Rayleigh quotient iteration. The proposed method’s performance and applicability are demonstrated on both simulated and real vibration signals
measured on an experimental test rig. The outcome of the study shows that the Rayleigh quotient iteration
is a potent tool for maximizing such complex condition monitoring indicators. Inspections over the filtered
signals reveal that the optimal filters promote particular signal patterns linked to a bearing fault in vibration
signals. The indicator estimated over the filtered signals is able to detect the bearing fault more robustly when compared to the raw signals.
blind filtering the of vibration signals. The key point is the optimization of the filter coefficients to maximize
the indicator of interest. The filter coefficients are optimized through Rayleigh quotient iteration. The proposed method’s performance and applicability are demonstrated on both simulated and real vibration signals
measured on an experimental test rig. The outcome of the study shows that the Rayleigh quotient iteration
is a potent tool for maximizing such complex condition monitoring indicators. Inspections over the filtered
signals reveal that the optimal filters promote particular signal patterns linked to a bearing fault in vibration
signals. The indicator estimated over the filtered signals is able to detect the bearing fault more robustly when compared to the raw signals.
| Original language | English |
|---|---|
| Title of host publication | International Conference on Noise and Vibration Engineering |
| Publisher | ISMA 2022 |
| Pages | 1-14 |
| Number of pages | 14 |
| Publication status | Published - 7 Sept 2022 |
| Event | 2022 ISMA International Conference on Noise and Vibration Engineering - KU Leuven, Leuven, Belgium Duration: 12 Sept 2022 → 14 Sept 2022 http://past.isma-isaac.be/isma2022/proceedings/program/ |
Conference
| Conference | 2022 ISMA International Conference on Noise and Vibration Engineering |
|---|---|
| Country/Territory | Belgium |
| City | Leuven |
| Period | 12/09/22 → 14/09/22 |
| Internet address |
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VLAAI1: Flanders Artificial Intelligence Research program (FAIR) – second cycle
1/01/24 → 31/12/28
Project: Applied
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