Instability issues and excessive vibration amplitudes are common problems encountered in large rotating machinery applications. In order to predict problems and overcome them, reliable rotor models are required. In the previous decades there has been a great improvement on finite element modeling,...

Instability issues and excessive vibration amplitudes are common problems encountered in large rotating machinery applications. In order to predict problems and overcome them, reliable rotor models are required. In the previous decades there has been a great improvement on finite element modeling, which was extensively used in rotordynamics problems. However, there is a great difficulty when bearings have to be considered, and the unbalance present in the machine must be known for good response prediction. This paper proposes a method of bearing and unbalance parameter estimation from measured responses at the bearings and considering a Finite Element model of the shaft. The proposed algorithm utilizes the adaptive filtering technique known as the RLS filter employing the QR decomposition. Simulations were conducted and good results were achieved for both stationary and speed-dependent bearing parameters.

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