Abstract
This paper presents a scheme that automatically generates hydraulic system fault symptoms by on-line processing of raw sensor data from a real hydraulic test rig. A condition-monitoring scheme based on the Unscented Kalman Filter (UKF) is developed on a validated model. The UKF algorithm estimates the system states and generates the residual errors. Four types of faults, which cannot be directly detected from current sensor values, are investigated in this work: external chamber leakage at either side of the actuator, internal leakage between the two hydraulic cylinder chambers, dynamic friction load, sudden loss of load and increment in load. Also, for each leakage scenario, three levels of leakage are used in the experiments. The developed UKF-based fault monitoring scheme is tested on the practical system while different fault scenarios are individually introduced to the system.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
F. Sassani, P. D. Lawrence, and M. Khoshzaban, “On-line monitoring a hydraulic arm using physical parameter tracking,” Proc. of the 2nd International Symposium on Intelligent Automation and Control/World Automation Congress, vol. 6, 1998.
A. Alleyne and L. Rui, “On the limitations of force tracking control for hydraulic servosystems,” Journal of Dynamic Systems, Measurement, and Control, vol. 121, no. 2, pp. 184–190, 1999.
Y. Lin, Y. Shi, and R. Burton, “Discrete-time H2-optimal output tracking control for an experimental hydraulic positioning control system,” International Journal of Advanced Mechatronic Systems, vol. 1, no. 3, pp. 168–174, 2009.
I. Moir and A. Seabridge, Aircraft Systems: Mechanical, Electrical and Avionics Subsystems Integration, Wiley, 2008.
J. J. Gertler, Fault Detection and Diagnosis in Engineering Systems, Marcel Dekker, 1998.
M. K. Zavarehi, P. D. Lawrence, and F. Sassani, “Nonlinear modeling and validation of solenoidcontrolled pilot-operated servovalves,” IEEE/ASME Trans. on Mechatronics, vol. 4, no. 3, 1999.
N. Niksefat and N. Sepehri, “A QFT fault-tolerant control for electrohydraulic positioning systems,” IEEE Trans. on Control Systems Technology, vol. 10, no. 4, pp. 626–632, 2002.
W. J. Crowther, K. A. Edge, and C. R. Burrows, “Fault diagnosis of a hydraulic actuator circuit using neural networks-an output vector space classification approach,” Proc. of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 212, no. 1, pp. 57–68, 1998.
S. Narasimhan and G. Biswas, “Model-based diagnosis of hybrid systems,” Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 37, no. 3, pp. 348–361, 2007.
B. Johnson, “An introduction to the design and analysis of fault-tolerant systems,” Fault-Tolerant Computer System Design, pp. 1–87, 1996.
L. An and N. Sepehri, “Hydraulic actuator leakage fault detection using extended Kalman filter,” International Journal of Fluid Power, vol. 6, no. 1, pp. 41–51, 2005.
L. An and N. Sepehri, “Hydraulic actuator leakage quantification scheme using extended Kalman filter and sequential test method,” Proc. of American Control Conference, pp. 6, 2006.
S. J. Julier and J. K. Uhlmann, “New extension of the Kalman filter to nonlinear systems,” Signal Processing, Sensor Fusion, and Target Recognition VI, Anonymous Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, USA, pp. 182–193, 1997.
S. J. Julier, J. K. Uhlmann, and H. F. Durrant-Whyte, “A new method for the nonlinear transformation of means and covariances in filters and estimators,” IEEE Trans. on Automatic Control, vol. 45, no. 3, pp. 477–482, 2000.
D. Simon, Optimal State Estimation: Kalman, H∞, and Nonlinear Approaches, Wiley-Interscience, 2006.
H. E. Merritt, Hydraulic Control Systems, John Wiley & Sons Inc, 1967.
L. Marton and B. Lantos, “Modeling, identification, and compensation of stick-slip friction,” IEEE Trans. on Industrial Electronics, vol. 54, no. 1, pp. 511–521, 2007.
O. Vahid, N. Eslaminasab, and MF. Golnaraghi, “Friction-induced vibration in lead screw systems: mathematical modeling and experimental studies,” Journal of Vibration and Acoustics, vol. 131, pp. 021003, 2009.
K. J. Astrom and C. De Wit, “Revisiting the LuGre friction model,” IEEE Control Systems Magazine, vol. 28, no. 6, pp. 101–114, 2008.
D. Karnopp, “Computer simulation of stick-slip friction in mechanical dynamic systems,” Journal of Dynamic Systems, Measurement and Control, vol. 107, no. 1, pp. 100–103, 1985.
L. Laval, N. K. M’sirdi, and J. C. Cadiou, “H∞ force control of a hydraulic servo-actuator with environmental uncertainties,” Proc. of IEEE International Conference on Robotics and Automation, pp. 1566–1571, 1996.
Author information
Authors and Affiliations
Corresponding author
Additional information
Recommended by Editorial Board member Guang-Hong Yang under the direction of Editorin-Chief Jin-Bae Park.
Mohammad Sepasi received the B.S. degree in Mechanical Engineering from Sharif University of Technology, Iran, in 2005, and the M.A.Sc. degree in Mechanical Engineering from the University of British Columbia, Canada, in 2007. Currently, he is a Ph.D. candidate at the Mechanical Engineering Department of the University of British Columbia. His research interests include robust control and system identification.
Farrokh Sassani received the B.Sc. degree from Sharif University of Technology, Tehran, Iran, and the M.Sc. and Ph.D. degrees from the Manufacturing and Machine Tools Division, Department of Mechanical Engineering, University of Manchester Institute of Science and Technology, Manchester, U.K. He is currently a professor of Mechanical Engineering at the University of British Columbia, Vancouver, BC, Canada. His research interests include modeling and simulation of systems, automation, and analysis and design of manufacturing processes. Dr. Sassani is a Fellow of the British Institute of Manufacturing and a Fellow of the American Society of Mechanical Engineers.
Rights and permissions
About this article
Cite this article
Sepasi, M., Sassani, F. On-line fault diagnosis of hydraulic systems using Unscented Kalman Filter. Int. J. Control Autom. Syst. 8, 149–156 (2010). https://doi.org/10.1007/s12555-010-0119-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12555-010-0119-6