Abstract

Bearing skidding is a frequent phenomenon in rotating machinery, which causes equipment motion instability and bearing wear failure. Due to the difficulties in the manufacture of high-speed flexible rotor test rig, measurement of bearing motion parameters and complex structure of angular contact ball bearing (ACBB), which makes the research on double-piece inner ring ACBB skidding challenging. This paper studies the ACBB skidding mechanism from the aspect of rotor characteristics, and first finds the resonance skidding phenomenon. Firstly, a high-speed flexible rotor test rig is designed and built to study the ACBB skidding mechanism, and the influence of foreign matter on the bearing cage slip rate is systematically studied. Then, the bearing cage speed considering the influence of lubricating oil pollution is accurately measured based on the adaptive fractional short-time Fourier transform. Finally, bearing skidding diagnosis under variable working conditions is realized based on the deep meta-transfer learning with feature enhanced generative adversarial network and average deflection power threshold. These proposed strategies systematically solve some problems in the research field of ACBB skidding, which has high practical significance and theoretical guidance value.

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