Detecting Mixed Gear Faults Using Scalar and Cyclostationary Indicators in an Industrial Settin

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.