Gear Fault Diagnosis Based on Second Order Cyclostationary Analysis

Abstract

Gearbox vibrations 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. The combinations of such components are best considered as cyclostationary. This paper discusses which second order cyclostationary statistics should be used for fault diagnosis of gear crack. The second order cyclostationary statistical methods are firstly introduced and then applied to fault diagnosis of gear crack. This approach is capable of completely extracting the characteristic fault frequencies related to the defect. Experiment results show that the second order cyclostationary statistics is powerful and effective in feature extracting and fault detecting for gearbox. The experimental result shows that the second order cyclostationary statistics can effectively diagnosis gear localized crack fault.