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The bearing fault diagnosis based on instantaneous angular speed (IAS) has been developed rapidly. However, it is difficult to identify the weak fault of bearings by using the variable reluctance sensor (VRS) as an encoder because of the lack of the high-frequency information in the modulation frequency of IAS. To overcome this shortcoming, a novel method based on the raw signal of the VRS is proposed for bearing diagnosis in this paper. The mechanism of bearing local fault signal response is analyzed by establishing the bearing outer ring fault model and the sensor signal response model, which are explored and verified by the fault simulation experiments. The results show that the gearwheel tooth-pass frequency is modulated by the outer ring fault characteristic frequency, and the defect size can be estimated by the double peaks in the high-frequency band. Moreover, compared with the acceleration signals, the defect size estimations based on the VRS are closer to the actual defect size, which verifies the effectiveness of the proposed method.

Modeling and Characteristic Analysis of Variable Reluctance Signal Variation of Rolling Bearing Outer Ring Fault