Combination of vibration analysis and Acoustic Emission measurements to better characterize damage and mechanical behaviour of aerospace high speed rolling bearing
Hebrard Yoann  1@  
1 : SKF - Aerospace [Saint-Vallier]
SKF

Designed to break the paradigm for efficiency, the new generation of engines promises double-digit reductions in fuel burn, as well as an unparalleled single-leap improvement in emissions and lower noise to fulfil societal environmental objectives for a more sustainable future. The end-use consumer and environmental policy requirements for aircrafts of the next generation translate into components with higher temperature and speed. Furthermore, new monitoring technics are needed to closely monitor rolling contact during testing of the next generation of aero engine bearing to check its behavior under the new application condition. Vibration analysis for condition assessment and fault diagnostics is widely used nevertheless interpretation and correlation of collected data is often cumbersome.

That is why combination of vibration analysis and acoustic emission techniques giving different types information in different frequency band can help to understand the behavior of new rolling bearing. This paper presents an experimental testing campaign on bearings with seeded defects. Correlation between low and high frequency signals with different strategy of signal acquisition are presented from signal processing step.

Real time transient analysis with feature extraction was done in parallel with streaming acquisition on both signals. Pattern recognition of individual AE signal is possible and were correlated with more traditional analysis based on signal enveloping vibration analysis. Continuous monitoring on finished duration were done to provide information on no stationary regime and also time of stabilization. Comparison between features extraction is done on damaged and defect free rolling bearing at several rotating speed and loading level.

 Keywords : high speed rolling bearing, experimental data, condition monitoring, vibration analysis, acoutic emission

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