Summary
Monitoring by vibration measurement and analysis is largely used in the industry for detection of defects in revolving parts of machines. The determination of good sensor positions is one of the main research goals in the field of predictive maintenance. This paper proposes a numerical methodology based on the FEM and spectral analysis in order to find the optimum sensor positions. Bearings are key components in the vibration propagation from moving parts to immobile ones. Two existing nonlinear models of bearings are recalled and implemented in a FE code. The obtained tangent stiffness matrices of bearings are then put in the global system to-study the dynamic behaviour. The dynamic response of the whole system under defect excitations is used to determine the optimum sensor placements for the defect detection in the predictive maintenance.
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Debray, K., Bogard, F. & Guo, Y.Q. Numerical vibration analysis on defect detection in revolving machines using two bearing models. Arch. Appl. Mech. 74, 45–58 (2004). https://doi.org/10.1007/BF02637208
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DOI: https://doi.org/10.1007/BF02637208