Cyclostationary Analysis Based Gear Fault Diagnosis

Abstract

Gearbox vibrations acquired by sensors are random cyclostationary signals, which are a combination of periodic and random processes due to the machine’s rotation cycle and interaction with the real world. Since the spectral structure of a gear vibration signal is mainly characterized by the interaction between the meshing harmonics and their sidebands, the spectral correlation density (SCD) function has been applied to gear monitoring. This approach is capable of completely extracting the fault characteristic frequencies related to the defect. This gives a desirable ability to detect the singularity characteristic of a signal precisely. This technique permits both fault detection and identification of the damaged gear. The experimental results show that the proposed method based on cyclostationary analysis can effectively diagnose the faults of gear.