Fault diagnosis of antifriction bearing of centrifugal pump based on random forest

  Objectives  The fault of centrifugal pump unit would influence the missions' accomplishment and the improvement of operational readiness. In order to solve the problem of detection and location of common faults of centrifugal pump units, a fault diagnosis method of antifriction bearing of centrifugal pump is presented.

  Methods  the vibration signal of the antifriction bearing was decomposed adaptively with the method of local characteristic-scale decomposition(LCD). The random forest was used for fault diagnose based on the sample entropy generated by the intrinsic scale component(ISC)extracting. Finally, combined with the fault diagnosis test, the correctness of the above method was verified based on the monitoring data of bearing fault injected into the centrifugal pump unit.

  Results  The results show that the diagnose method based on LCD and random forest can effectively diagnose the fault mode of the antifriction bearing of centrifugal pump.

  Conclusions  The study in this paper can lay a foundation for the improvement of equipment fault diagnosis capability, and provide technical support for the establishment of centrifugal pump fault prediction and health management system.