Effective Identification of Cyclic Excitation and Resonance in Non-stationary Gearbox Vibration Monitoring
Abstract
Since as a rotating machinery, the gearbox is an important source of vibration, the
identification of signals and parameters of the component content of the gearbox is necessary
for the monitoring of the system. Within the mechanism, the rotation of elements with pe riodic
discrete geometries (bearings, gears, turbines, ...) is the origin for potential excitations which
are commonly cyclic. These excitations are therefore characterized by frequencies that evolve
with rotation speed that reconstructing them, is equivalent to an inverse problem or an
identification problem. The main problem is to find the right external excitation conditions
particularly in torque to reveal behaviors that are either resonances (a well-known linear
problem and treated by identification) or internal excitations (less known and less well-
treated). The difficulty here lies effectively in non-stationary operating conditions for a good
exploitation of time and angular Fourier Transform framework
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