Prognostics and Health Management of an Electro-Hydraulic Servo Actuator
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Abstract
Electro-Hydraulic Servo Actuators (EHSA) is the principal technology used for primary flight control in new aircrafts and legacy platforms. The development of Prognostic and Health Management technologies and their application to EHSA systems is of great interest in both the aerospace industry and the air fleet operators.
This paper presents the results of an ongoing research activity focused on the development of a PHM system for fly-by-wire primary flight EHSA. One of the key features of the research is the implementation of a PHM system without the addition of new sensors, taking advantage of sensing and information already available. This choice allows extending the PHM capability to the EHSAs of legacy platforms and not only to new aircrafts. The enabling technologies borrow from the area of Bayesian estimation theory and specifically particle filtering and the information acquired from EHSA during pre-flight check is processed by appropriate algorithms in order to obtain relevant features, detect the degradation and estimate the Remaining Useful Life (RUL). The results are evaluated through appropriate metrics in order to assess the performance and effectiveness of the implemented PHM system
How to Cite
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anomaly detection, particle filtering, failure prognosis, primary flight command, EHSA
Brown, D., Georgoulas, G., Bae, H., Vachtsevanos, G.,Chen, R., Ho, Y.H., Tannenbaum, G., & Schroeder,J.B. (2009a). Particle filter based anomaly detection foraircraft actuator systems. Aerospace conference, 2009 th th IEEE , pp.1-13, March 7 -14 .
Brown, D., Georgoulas, G., Bole, B., Pei, H. L., Orchard,M., Tang, L., Saha, B., Saxena, A., Goebel, K., &Vachtsevanos, G. (2009b). Prognostics Enhanced Reconfigurable Control of Electro-Mechanical Actuators. Annual conference of the Prognostics and Health Management Society PHM09, San Diego, USA,
Byington, C.S., Watson, M., & Edwards, D. (2004). Data-driven neural network methodology to remaining life predictions for aircraft actuator components. 2004 IEEE Aerospace Conference, Proceedings, vol. 6, pp.35813589, March 6 th – 13th
International Air Transport Association (IATA) (2011). Airline Maintenance Cost Executive Commentary - An exclusive benchmark analysis (FY2009 data) by IATA’s Maintenance Cost Task Force
Jacazio, G. (2008). The Evolution of Fly-by-Wire Flight Control Systems. Guest speaker presentation at the IASTED conference on Modelling, Identification, and Control, Innsbrück, Austria , February 11 th - 13th
Jacazio, G., Maggiore, P., Della Vedova, M. & Sorli, M. (2010). Identification of Precursors of Servovalves Failures for Implementation of an Effective Prognostics. Proceedings of the 4th International Conference on Recent Advances in Aerospace Actuation Systems and Components, Toulouse, France, May 5 th – 7th .
Jacazio, G., Mornacchi, A., & Sorli, M. (2015). Development of a prognostics and health management system for electrohydraulic servoactuators of primary flight controls. 5 th International Workshop on Aircraft System Technologies AST2015, Hamburg, Germany, February 24 th – 25th .
Marla, L., Vaaben, B., Barnhart, C. (2011) Integrated disruption management and flight planning to trade off delays and fuel burn; Report 16.2011 - DTU Management Engineering; December 2011 Martini, L. J. (1984), Reciprocating Seals - Pistons and Cylinders. In CRC Press, Practical Seal Design (pp. 108-131). New York
Mornacchi, A., & Vignolo, M. (2014). Health Management System for the Hydraulic Servoactuators of Fly-by-Wire Primary Flight Control Systems. European Conference of Prognostics and Health Management Society PHME14, Nantes, France, July 8 th – 14th .
Narasimhan, S., Roychoudhury, I., Balaman, E., & Saxena, A. (2010). Combining Model-Based and FeatureDriven Diagnosis Approaches – A Case Study on Electromechanical Actuators. 21st International Workshop on the Principles of Diagnosis (DX-10), Portland, USA, October 13 th - 16th .
Orchard, M., Kacprzynski, G., Goebel, K., Saha, B., & Vachtsevanos, G. (2008). Advances in Uncertainty Representation and Management for Particle Filtering Applied to Prognostics. Annual Conference of the Prognostics and Health Management Society PHM08, Denver, USA, October 6 th – 9th .
Orchard, M., & Vachtsevanos, G. (2009). A Particle Filtering Approach for On-Line Fault Diagnosis and Failure Prognosis. Transactions of the Institute of Measurement and Control, vol. 31, no. 3-4, pp. 221246.
Pohl, T., (2013). Cost per hour of downtime per aircraft is ~ 10,000 USD+ more, in SAP for Aerospace & Defense Roemer, M., Byington, C., Kacprszynski, G., Vachtsevanos, G., & Goebel, K. (2011). Prognostics, in Systems Health Management with Aerospace Applications. Wiley, pp. 281-295 Saxena, A., Celaya, J., Balaban, E., Goebel, K., Saha, B., Saha, S., & Schwabacher, M. (2008). Metrics for evaluating performance of prognostic techniques. International Conference on Prognostics and Health Management, pp.1,17, October 6 th - 9th
Urata, E. (2007a). On the torque generated in a servo valve torque motor using permanent magnets. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. vol. 221 (Issue 5), pp. 519-525
Urata, E. (2007b). Influence of unequal air-gap thickness in servo valve torque motors. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. vol. 221 (Issue 11), pp. 1287-1297
Vachtsevanos, G., Lewis, F., Roemer, M., Hess, A. & Wu, B. (2006). Intelligent Fault Diagnosis and Prognosis for Engineering Systems. John Wiley & Sons, Inc. Yeager, J. (1998). Implementation and Testing of Turbulence Models for the F18-HARV Simulation. NASA CR-1998-206937, Lockheed Martin Engineering & Sciences.
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