Because frequency conversion characteristic(caused by the variable vehicle speed) existed in automobile bearing fault online detection, and the general fault detection method could not be adapted to the frequency conversion characteristic, an online fault detection method based on dynamic time window was proposed. The vehicle driving state was analyzed, and the relationship between speed and hub bearing speed was given. The determination rules of dynamic time window was given according to the characteristic speed. Wignerville distribution fault detection model based on characteristic speed was constructed. Finally, the proposed algorithm was tested by collecting real vehicle data.The results show that the fixed time window detection algorithm is suitable for offline bearing fault detection, and the dynamic time window detection algorithm based on characteristic speed is suitable for online fault detection.