Cage fault diagnosis method based onroller spacing variation recognition with full-cycletime domain regression

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Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (17) : 45-50.

LI Xiuwen1,2, TANG Deyao2, YANG Ronghua1,2

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Abstract

Aiming atthe problem of large amount of non-metal cages being used to replace metal ones in rail transitfield to make it unable to produce periodic metal collision information after cages having faults for their recognition, a cage fault diagnosis method based on roller spacing variation recognition with the whole periodic time domain regression was proposed.Firstly, vibration signals containing stress information of roller passing outer ring’s load-bearing zone were collected, and sampling frequency was tracked and corrected.Then these signals were full-cycled according to cage outer cycle.At the same time, outer-ring frequencies and side frequency information of roller jitter werereserved forfiltering in frequency domain.Finally, per roller spacing information was obtained using the maximum value principle to identify if cage fault happening.Simulation and signals of actual rolling bearings with non-metallic cage showed that the proposed method can be used to effectively extract useful information reflectingif per roller spacing is abnormal to realize fault diagnosis of cages.

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time domain regression / cage / fault diagnosis

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LI Xiuwen1,2, TANG Deyao2, YANG Ronghua1,2. Cage fault diagnosis method based onroller spacing variation recognition with full-cycletime domain regression[J]. Journal of Vibration and Shock, 2019, 38(17): 45-50

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