OPTIMISATION OF BEARING DIAGNOSTIC TECHNIQUES USING SIMULATED AND ACTUAL BEARING FAULT SIGNALS

By D. Ho, R. Randall. 2000

576 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/af867bcdd7fafaa76251b6e4ea0a73b364996119

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. P. W. Tse
2. Colin H. Hansen
3. Sarabjeet Singh
4. Carl Q. Howard
5. Jianbo Yu
6. Xuefeng Chen
7. Xingqing Wang
8. J. Y. Zhang

In Control and Systems Engineering

1. P. W. Tse
2. Sarabjeet Singh
3. Colin H. Hansen
4. Carl Q. Howard
5. Jianbo Yu
6. Xuefeng Chen
7. Ruqiang Yan
8. Robert X. Gao

In Mechanical Engineering

1. Sarabjeet Singh
2. Colin H. Hansen
3. Carl Q. Howard
4. P. W. Tse
5. Jianbo Yu
6. Shuting Li

Citations in the corpus

• An extensive review of vibration modelling of rolling element bearings with localised and extended defects (2015, methodology): “[48] also modelled the localised 212 defect-induced vibration signals as a series of impulse responses of a 1-DOF system.”
• Machine fault diagnosis through an effective exact wavelet analysis (2004, background): “Hence, the fault-related impulses are difficult to distinguish from the broad spectrum, because they may be overwhelmed or even buried by other larger structural vibrations and background noise [27].”
• Bearing performance degradation assessment using locality preserving projections (2011, methodology): “…for spectrum analysis are graphical presentation of spectrum, frequency filters, envelop analysis, minimum variance cepstrum (Choi & Kim, 2007; Ho & Randall, 2000; Randall, Antoni, & Chobsaard, 2001; Stack, Harley, & Habetler, 2004), etc. Hilbert transform, which is a useful tool for envelope…”