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Project

Condition monitoring under varying operating and environmental conditions

Vibration-based condition monitoring plays a lead role in fault detection in bearings and gears. In the case of gearboxes, gears (as long as they are in contact, without backlash) usually provide a strong periodic signal at their meshing frequency (and its harmonics) masking the usually weak signals emitted by faulty bearings, which are random signals due to the fact that the rolling element movement presents slip. Bearing signals are often characterized as cyclostationary based on the fact that they present some characteristic properties. Diagnostic methodologies have reached maturity in the steady-state operating conditions, but several issues are still open in the case of machinery operating under time-varying operating conditions, as in the case of wind turbine epicyclical gearboxes. Thus the goal of the Ph.D. is the development of novel signal processing tools focusing on the accurate fault detection and diagnosis of faults in rotating machinery operating under varying speed and environmental conditions and towards the quantification of the size of the defect. The methodologies will be tested, evaluated, and valuated on signals captured on dedicated test rigs as well as on real signals.

Date:1 Sep 2021 →  Today
Keywords:Condition Monitoring, Signal processing, Fault detection and diagnosis, varying conditions
Disciplines:Engineering instrumentation, Dynamics, vibration and vibration control
Project type:PhD project