Hydraulic Actuator Leakage Fault Detection using Extended Kalman Filter

Abstract This paper presents the application of extended Kalman filter (EKF) in order to identify leakage faults in hydraulically powered actuators. A hydraulic actuator can suffer from two types of leakages: internal or cross-port leakage at the piston seal and, external leakage at the shaft seal or the connecting pipes. An EKF-based estimator is constructed that includes complete nonlinear models of hydraulic functions as well as inevitable stick-slip friction in the actuator. It is shown that, firstly, under normal (no-fault) operating condition, the developed estimator closely predicts the states of the system, using only a few basic measurements. Secondly, in the presence of leakage faults, the level of residual errors between the estimated and the measured line pressures, increase significantly indicating the occurrence of faults. Thirdly, different leakage types can be identified by mapping the residual errors changes. Experiments are performed on a laboratory-based hydraulic actuator circuit. The results demonstrate the efficacy of the proposed EKF-based fault detection scheme to promptly and reliably respond to actuator's external and internal leakage faults.

[1]  Nariman Sepehri,et al.  Fault-tolerant control of a servohydraulic positioning system with crossport leakage , 2005, IEEE Transactions on Control Systems Technology.

[2]  D. N. Shields,et al.  Fault detection for bilinear systems with application to a hydraulic system , 1994, 1994 Proceedings of IEEE International Conference on Control and Applications.

[3]  Nariman Sepehri,et al.  Simulation and Experimental Studies of Gear Backlash and Stick-Slip Friction in Hydraulic Excavator Swing Motion , 1996 .

[4]  Farrokh Sassani,et al.  Nonlinear modeling and validation of solenoid-controlled pilot-operated servovalves , 1999 .

[5]  Nariman Sepehri,et al.  Fault detection in electro-hydraulic servo-positioning systems using sequential test of Wald , 2002, IEEE CCECE2002. Canadian Conference on Electrical and Computer Engineering. Conference Proceedings (Cat. No.02CH37373).

[6]  S. Haykin Kalman Filtering and Neural Networks , 2001 .

[7]  D. N. Shields,et al.  Application of a robust nonlinear fault detection observer to a hydraulic system , 1997, 1997 European Control Conference (ECC).

[8]  Nariman Sepehri,et al.  Fault detection and isolation in fluid power systems using a parametric estimation method , 2002, IEEE CCECE2002. Canadian Conference on Electrical and Computer Engineering. Conference Proceedings (Cat. No.02CH37373).

[9]  Carlos Canudas-de-Wit,et al.  Friction compensation for an industrial hydraulic robot , 1999 .

[10]  A. Jazwinski Stochastic Processes and Filtering Theory , 1970 .

[11]  Victor A. Skormin,et al.  On-line diagnostics of a self-contained flight actuator , 1994 .

[12]  Clifford R. Burrows,et al.  Fault diagnosis of a hydraulic actuator circuit using neural networks—an output vector space classification approach , 1997 .

[13]  P. Frank On-line fault detection in uncertain nonlinear systems using diagnostic observers: a survey , 1994 .

[14]  Nacer K. M'Sirdi,et al.  H/sub /spl infin//-force control of a hydraulic servo-actuator with environmental uncertainties , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[15]  Amit Shukla,et al.  Feedback design for robust tracking and robust stiffness in flight control actuators using a modified QFT technique , 1999 .

[16]  Victor A. Skormin,et al.  On-line diagnostics of a variable displacement pump of a flight actuation system , 1995, Proceedings of the IEEE 1995 National Aerospace and Electronics Conference. NAECON 1995.

[17]  Nariman Sepehri,et al.  Parametric fault diagnosis for electrohydraulic cylinder drive units , 2002, IEEE Trans. Ind. Electron..

[18]  Amit Shukla,et al.  Feedback design for robust tracking and robust stiffness in flight control actuators using a modified QFT technique , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[19]  D. N. Shields,et al.  Application of a robust nonlinear fault detection observer to a hydraulic system , 1997 .

[20]  J. L. Roux An Introduction to the Kalman Filter , 2003 .

[21]  Saeid Habibi,et al.  Viscous Damping Coefficient and Effective Bulk Modulus Estimation in a High Performance Hydrostatic Actuation System using Extended Kalman Filter , 2003 .

[22]  Peter I. Corke,et al.  A pressure-based, velocity independent, friction model for asymmetric hydraulic cylinders , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[23]  Nariman Sepehri,et al.  Hydraulic actuator circuit fault detection using extended Kalman filter , 2003, Proceedings of the 2003 American Control Conference, 2003..

[24]  Rolf Isermann,et al.  Supervision, fault-detection and fault-diagnosis methods — An introduction , 1997 .

[25]  Byung-Jae Kwak,et al.  Nonlinear system identification of hydraulic actuator friction dynamics using a finite-state memory model , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[26]  Carlos Canudas de Wit,et al.  A new model for control of systems with friction , 1995, IEEE Trans. Autom. Control..

[27]  Dominik Füssel,et al.  Supervision, Fault-Detection and Fault-Diagnosis Methods , 1999 .