Identification Procedures as Tools for Fault Diagnosis of Rotating Machinery

Abstract

System identification procedures offer the possibility to correct erroneous models, based on measurement data. Recently, this conventional field of application is being extended to fault detection and system diagnosis. In contrast to conventional approaches, identification procedures try to establish an unequivocal relation in between the damage and specific mechanical parameters, based on a suitable model. Furthermore, they can be employed during normal operation of the machinery. In this paper, several identification procedures on the basis of the Extended Kalman Filter are introduced and employed for model-based fault detection. Their feasability is proved by several examples. First, it is shown that the crack depth of a simulated Jeffcott-rotor can be calculated correctly. Then, the procedures are utilized to determine the crack depth of a rotor test rig. Finally, it is proved that identification procedures can be employed for the determination of unbalances without having to apply test masses.