Elastodynamics based Modelling of Acoustic Emission for Earlier Bearing Damage Detection

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Published Nov 5, 2024
Anurag Bhattacharyya Krishnan Thyagarajan Jin Yan Kevin Pintong Qiushu Chen Joseph Lee Peter Kiesel Kai Goebel

Abstract

It is crucial for many applications to detect bearing damage as early as possible to allow for scheduling of maintenance with lead times that minimize operational disruption. State of the practice is the detection of spalling but damage initiates prior to spalling as subsurface and surface cracks. Such damage is much harder to detect and to model. This study proposes a unique application of the nanofrictional Prandtl-Tomlinson model to predict macroscopic acoustic emission (AE) signals that occur at cracked interfaces under relative motion. The study integrates large deformation modelling of structures with elastodynamic simulations to investigate early AE signals generated under different bearing rotational speeds. Experimental studies are carried out to measure acoustic vibrations from metal-metal surface friction using fiber optic sensors and compared to those predicted by the model. Broad agreement of results highlights the validity of this framework.

How to Cite

Bhattacharyya, A., Thyagarajan, K. ., Yan, J., Pintong, K., Chen, Q., Lee, J., Kiesel, P., & Goebel , K. . (2024). Elastodynamics based Modelling of Acoustic Emission for Earlier Bearing Damage Detection. Annual Conference of the PHM Society, 16(1). https://doi.org/10.36001/phmconf.2024.v16i1.3971
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Keywords

Elastodynamics, Acoustic Emission, Bearing Damage Detection, Finite Element Analysis, Prandtl-Tomlinson Model

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Section
Technical Research Papers

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