More often then not, the rolling element bearings of rotating machinery are the mechanical components that are first prone to premature failure. Early warning of an impending bearing failure is vital to the safety and reliability of high-speed turbo-machinery. Presently, vibration monitoring is one of the most applied procedures in on-line damage and failure monitoring of rolling element bearings. This paper presents results from an experimental rotor-bearing test rig where quantified damage was induced in the supporting tapered ball bearings. Subsequently the vibration signature due to damage at the inner race of the bearing is examined. Four on-line vibration signature analyzing schemes are used concomitantly: (i) time averaging, (ii) frequency domain analysis, (iii) joint time-frequency analysis (Wigner-Ville and wavelet transforms) and (iv) chaotic vibration analysis (modified Poincare diagrams). The size/level of the damage is corroborated with the vibration amplitude and the resulting relationships are linearized to provide quantification criteria for bearing progressive failure prediction. The results from the above mentioned methodologies are compared for accuracy and redundancy, thus increasing the reliability for early detection of bearing damage and failure. It is shown that the use of the modified Poincare map can provide an effective way for identification and quantification of bearing damage in rolling element bearings.

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