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Journal of Failure Analysis and Prevention

, Volume 18, Issue 2, pp 330–341 | Cite as

Investigation on Axial Displacement Fault Mechanism Based on Dynamic Characteristic Coefficients Identification of Tilting-Pad Thrust Bearing

  • Binbin Liu
  • Weimin Wang
  • Ya Zhang
  • Xing Shao
  • Weibo Li
Technical Article---Peer-Reviewed
  • 92 Downloads

Abstract

To prevent the thrust bearing damage faults, the thrust bearing pad temperature and the static axial displacement variation are usually monitored and cared about, but axial vibration caused by axial dynamic excitation can also result in the severe rubbing. An electric oil pump system with overflow valve is designed on a similar industrial centrifugal compressor test-rig to apply the axial low-frequency excitation from 3 to 7 Hz, and the axial and radial vibration response amplitudes are analyzed. Then, the stiffness and damping coefficients of tilting-pad thrust bearing (TPTB) are identified by instrumental variable filter (IVF) algorithm to reveal the mechanism of TPTB dynamic characteristics affecting axial vibration. Finally, a fault case about surge and the rubbing of thrust bearing is studied. Compared with axial vibration, radial vibration does not directly correlate to axial excitation, and the axial frequency spectrum is an effective method to diagnose axial displacement faults; the static axial load, the dynamic excitation amplitude and the excitation frequency all exert influence on thrust bearing dynamic characteristics and axial vibration response. The research results can guide the design of thrust bearings and help to diagnose the axial displacement faults, while the test device and method can be used to measure the static and dynamic characteristics of thrust bearings.

Keywords

Axial displacement fault IVF algorithm Thrust bearing Dynamic characteristics 

Notes

Acknowledgments

This research has been supported by the National Natural Science Foundation of China (51775030) and the Fundamental Research Funds for the Central Universities (BHYC1703A).

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Copyright information

© ASM International 2018

Authors and Affiliations

  1. 1.Beijing Key Laboratory of Health Monitoring Control and Fault Self-recovery for High-end MachineryBeijing University of Chemical TechnologyBeijingChina

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