Model based unbalance monitoring using augmented observer in rotor systems under the consideration of gyroscopic effect

Unbalance forces are a crucial issue in rotor systems. Often it is of interest to monitor the states of unbalances while the rotor is running in order to prevent damages to the rotor system. For the model based unbalance monitoring a rotor model is required to represent the behavior of the rotor system and the influences of the unbalances. The feasibilities of the methods are often limited by the accuracy of the system model. Accurate physical model is often hard to build especially for large scale rotor systems with unknown physical properties. In case of rotor systems with large discs, the gyroscopic effect is not negligible. It results in a rotary frequency dependent system behavior and thus makes the modeling problem more complicated. Besides the modeling problems, disturbances from initial unbalances and rotor bow are also issues to be considered in the unbalance monitoring. In this paper we formulate the disturbances and gyroscopic effect as unknown inputs, which are widely investigated in the fault detection processes and use the model of non-rotating rotor as basis for the unbalance monitoring. Augmented observer, which takes sinusoidal vibrations into consideration is used for the unbalance monitoring. The application of the method on a rotor test rig is presented in this paper.

[1]  Zhentao Wang,et al.  Observer design for unbalance excited rotor systems with gyroscopic effect , 2012, 2012 IEEE International Conference on Mechatronics and Automation.

[2]  Arne Wahrburg,et al.  Consideration of Gyroscopic Effect in Fault Detection and Isolation for Unbalance Excited Rotor Systems , 2012 .

[3]  Jie Chen,et al.  Uncertainty Modelling and Robust Fault Diagnosis for Dynamic Systems , 2000 .

[4]  Megan E. Schwamb,et al.  PLANET HUNTERS. V. A CONFIRMED JUPITER-SIZE PLANET IN THE HABITABLE ZONE AND 42 PLANET CANDIDATES FROM THE KEPLER ARCHIVE DATA , 2013, 1301.0644.

[5]  Maurice Adams,et al.  Rotating Machinery Vibration: From Analysis to Troubleshooting , 2000 .

[6]  W. Marsden I and J , 2012 .

[7]  J. Si,et al.  Fault isolation filter design for linear time-invariant systems , 1997, IEEE Trans. Autom. Control..

[8]  Jie Chen,et al.  Modelling of uncertainties for robust fault diagnosis , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[9]  Silvio Simani,et al.  Model-Based Fault Diagnosis Techniques , 2003 .

[10]  Richard Markert,et al.  Validation of online diagnostics of malfunctions in rotor systems , 2000 .

[11]  C. Johnson Further study of the linear regulator with disturbances--The case of vector disturbances satisfying a linear differential equation , 1970 .

[12]  Stephan Rinderknecht,et al.  Augmented Observer for Fault Detection and Isolation (FDI) in Rotor Systems , 2012 .

[13]  Stephan Rinderknecht,et al.  Application of Augmented Observer for Fault Diagnosis in Rotor Systems , 2013 .

[14]  Jie Chen,et al.  Optimal unknown input distribution matrix selection in robust fault diagnosis , 1993, Autom..

[15]  R. Markert,et al.  Model Based Fault Identification in Rotor Systems by Least Squares Fitting , 2001 .

[16]  Giancarlo Genta,et al.  Dynamics of Rotating Systems , 2005 .

[17]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems: theory and application , 1989 .

[18]  Stephan Rinderknecht,et al.  Observer design for rotating shafts excited by unbalance , 2012 .

[19]  Jun Ni,et al.  Extended Influence Coefficient Method for Rotor Active Balancing During Acceleration , 2004 .

[20]  R. J. Patton,et al.  A Matrix Pencil Approach to Fault Detection and Isolation Observers , 1996 .

[21]  Rolf Isermann,et al.  Fault-Diagnosis Systems , 2005 .

[22]  Nicolò Bachschmid,et al.  Identification of multiple faults in rotor systems , 2002 .

[23]  Jianjun Shi,et al.  Imbalance Estimation for Speed-Varying Rigid Rotors Using Time-Varying Observer , 2001 .

[24]  Paul M. Frank,et al.  Issues of Fault Diagnosis for Dynamic Systems , 2010, Springer London.

[25]  Jennie Si,et al.  Fault isolation filter design for linear systems , 1994, AIAA/IEEE Digital Avionics Systems Conference. 13th DASC.