Model Based Fault Identification in Rotor Systems by Least Squares Fitting

In the present paper a model based method for the on-line identification of malfunctions in rotor systems is proposed. The fault-induced change of the rotor system is taken into account by equivalent loads which are virtual forces and moments acting on the linear undamaged system model to generate a dynamic behaviour identical to the measured one of the damaged system. By comparing the equivalent loads reconstructed from current measurements to the pre-calculated equivalent loads resulting from fault models, the type, amount and location of the current fault can be estimated. The identification method is based on least squares fitting algorithms in the time domain. The quality of the fit is used to find the probability that the identified fault is present. The effect of measurement noise, measurement locations, number of mode shapes taken into account etc., on the identification result and quality is studied by means of numerical experiments. Finally, the method has also been tested successfully on a real test rig for some typical faults.