A Fault Detection Method Based on Bearing Dynamics with Multi-frequency Sinusoidal Signal

Bearing is a common and important component in the industry, and it is crucial to detect and diagnose its working condition. According to the characteristic the motion process of the bearing that is a periodic nonlinear system with sinusoidal input, a bearing fault detection method based on the nonlinear system with multi-frequency sinusoidal input is proposed. Through the dynamics modeling of the motion for the bearing, it is found that its input and output have the characteristics of almost periodic function. Using the periodogram-based asymptotic local fault detection method, the fault detection problem is transformed into a hypothesis test problem, and a threshold is obtained by the given confidence and the degree of freedom of a specific frequency matrix. The method can effectively and quickly monitor the early minor faults in strong noise environment. The realization and performance of this bearing detection method are illustrated by the simulated vibration signal of the bearing.