A deep learning approach towards diagnostics of bearings operating under non-stationary conditions
Faults in bearings usually manifest as marginal defects that intensify over time, allowing for well-informed preventative actions with early Fault Detection and Diagnosis (FDD) protocols. Detection of the fault begins with capturing, for example, acceleration signals from a machine. Traditionally, h...
| Main Author: | |
|---|---|
| Other Authors: | |
| Language: | en_US |
| Published: |
University of Pretoria
2020
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/2263/73452 Baggerohr, S 2019, A deep learning approach towards diagnostics of bearings operating under non-stationary conditions, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/73452> |