On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques
Chrissanthi Angeli* and Avraam Chatzinikolaou**
*Department of Mathematics and Computer Science, Technological Institute of Piraeus, Konstantinoupoleos 38, N. Smirni, GR-171 21 Athens, Greece
**S. Patsi 62, GR-118 55 Athens, Greece
The development of on-line fault detection methods for drive and control systems is of main importance for the modern production technology. Modelling information improves the reliability of the diagnostic method when it is involved in a fault detection system. In this paper, the use of modelling information for the fault detection of hydraulic driven machines as well as for the compensation of incipient faults is presented. For this purpose a suitable implementation environment was developed that allows the on line interaction of real time data and simulation results and makes possible their direct effect to the actual system.
-  R. Patton, P. Frank, and R. Clark, “Issues in Fault Diagnosis for Dynamic Systems,” Springer-Verlag, 2000.
-  J. Chen and R. Patton, “Robust Model Based Fault Diagnosis for Dynamic Systems,” Kluwer Academic Publishers, 1999.
-  J. Korbicz, J. Koscielny, Z. Kowalczuk, and W. Cholewa, “Fault Diagnosis: Models, Artificial Intelligence, Applications,” Springer Verlag, Berlin, 2004.
-  R. Isermann, “Model-based Fault Detection and Diagnosis: Status and Applications,” Annual Reviews in Control, Vol.29, pp. 71-85, 2005.
-  R. S. Mangoubi and A. M. Edelmayer, “Model based fault detection: the optimal past, the robust present and a few thoughts on the on the future,” In Proc. Safeprocess 00, Budapest, 2000.
-  Z. Chen and Y. Lu, “State Monitoring and Fault Diagnosis for Hydraulic systems,” Pneumatics and Hydraulics, Vol.2, pp. 3-7, 1995.
-  J. Koscielny and M. Syfert, “Fuzzy Logic Application to Diagnostics of Industrial Processes,” Proc. Safeprocess 03, pp. 711-717, Washington, U.S.A., 2003.
-  R. Oehler, A. Shoenhoff, and M. Schreiber, “On-line model-based fault detection and diagnosis for a smart aircraft actuator,” Proc. Safeprocess 1997, pp. 575-580, Kingston upon Hull, U.K., 1997.
-  P. Rzepiejewski, M. Syfert, and S. Jegorov, “On-line Actuator Diagnosis Based on Neural Models and Fuzzy Reasoning: The DAMADICS Benchmark Study,” Proc. Safeprocess 03, Washington, U.S.A. pp. 981-986, 2003.
-  C. Angeli and A. Chatzinikolaou, “Troubleshooting in Hydraulic Systems using knowledge-based Methods,” Int. Journal of Engineering Simulation , Vol.6, No.1, pp. 24-29, 2005.
-  S. Mundry and C. Stammen, “Condition Monitoring for fluid technology,” o+p Oelhydraulic and Pneumatic, Vol. 46, No.2, 2002.
-  H. Straky, M. Muenchhof, and R. Isermann, “Model-based fault detection and diagnosis for hydraulic braking systems,” Safeprosess 2003, pp. 307-312, Washington, U.S.A., 2003.
-  H. Murrenhoff, T. Meindorf, and C. Stammen, “Condition Monitoring in Fluid Technology,” Proc. of 4th Int. Fluid Power Conf., Vol.2, pp.219-244, Dresden, 2004.
-  T. Hong-Zhou and S. Nariman, “On Condition Monitoring of Pump pressure in a Servo-Driven System,” Proc. of the 2001 American Control Conf., pp. 4478-4483, 2001.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.