Rolling element bearings (REBs) are typical tribological
components used widely in rotating machines. Their failure
could cause catastrophic damage. Therefore, condition
monitoring of bearings has always had great appeal for
researchers. Usually, the detection and diagnostics of
incipient bearing faults are achieved by characterising the
weak periodic impacts induced by the collision of defective
bearing components. However, race wear evolution, which
is inevitable in bearing applications, can affect the contact
between bearing elements and races, thereby decreasing the
impact magnitudes and impeding detection performance.
In this paper, the effect of wear evolution on the condition
monitoring of rolling bearings is firstly analysed based on
internal clearance changes resulting from the wear effect.
Then, an experimental study is ingeniously designed to
simulate wear evolution and evaluate its influence on wellknown
envelope signatures according to measured vibrations
from widely used tapered roller bearings. The fault type is
diagnosed in terms of two indices: the magnitude variation
of characteristic frequencies and the deviation of such
frequencies. The experimental results indicate a signature
decrease with regard to wear evolution, suggesting that
accurate severity diagnosis needs to take into account both the
wear conditions of the bearing and the signature magnitudes.
Condition Monitoring for Roller Bearings of Wind Turbines Based on Health Evaluation under Variable Operating States
