A model-based technique to identify lubrication condition of hydrodynamic bearings using the rotor vibrational response

Faults related to hydrodynamic bearing can imply in high maintenance costs when late-detected and even the total shutdown of system. Thus, techniques early fault diagnosis have relevance reliability rotating machinery. However, a common caused by inadequate oil supply has not yet received appropriate attention. This paper presents new approach model identify starved or excessive bearings. The developed identification technique is model-based process that uses rotor vibration signal access lubrication. Numerical tests were performed results showed proposed method satisfactorily estimate flow rate bearings under flooded lubrication conditions, thus representing useful promising tool for condition monitoring applied