Abstract
In this paper, an innovative approach is presented to enhance gear fault diagnosis using the cyclostationarity method. The first part of this study focuses on simulating gear signals under various conditions, allowing exploration of signal characteristics in vibration measurements. Spectral analyses and statistical calculations are performed to extract both classical and cyclostationary indicators. In the second part, the cyclostationarity method is applied to signals recorded at the gearbox bearings, clearly revealing the presence of faults. The results from these experiments demonstrate that cyclostationarity indicators can be leveraged to improve the prediction of signal roughness during the production process. This approach thus opens up new possibilities to enhance the reliability of vibration measurements and refine gear fault diagnosis.
References
- Antoni, J., Bonnardot, F., Raad, A., & El Badaoui M (2004) Cyclostationary modelling of rotating machine vibration signals. Mech Syst Signal Proc 18(6):1285–314.
- Antoni, J. (2007). Cyclic spectral analysis of rolling-element bearing signals: facts and fictions. Sound Vib 304:497–529.
- Antoni, J. (2009). Cyclostationarity by examples. Mech Syst Signal Proc 23:987–1036.
- Boulenger, A, Pachaud, C. et al (1998). Vibratory diagnosis in maintenance préventive. ISBN 2100041053, Dunod, Paris, pp 239-295
Details
| Primary Language | English |
|---|---|
| Subjects | Environmental and Sustainable Processes |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | December 31, 2023 |
| Publication Date | December 30, 2023 |
| Published in Issue | Year 2023Volume: 26 |
