Bearings Fault Diagnosis Based on Second Order Cyclostationary Analysis

Rolling element bearings 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 bearing. The second order cyclostationary statistical methods are firstly introduced and then applied to fault detection of bearing. 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 rolling element bearings.