Results of a Feasibility Study of a Prognostic System for Electro-Hydraulic Flight Control Actuators
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Published
Mar 25, 2021
Sylvain Autin
Andrea De Martin
Giovanni Jacazio
Jérôme Socheleau
George Vachtsevanos
Abstract
Electro-Hydraulic Servo-Actuators (EHSA) are currently the most used actuation technology for primary flight control systems of civil and military aircrafts. Although some alternatives have emerged in the last decade, such as electromechanical or electro-hydrostatic solutions, electrohydraulic systems are still considered the most effective technology in flight-critical application of new commercial aircrafts. Moreover, the vast majority of aircraft currently in service are equipped with this technology. Considering the number of actuators typically employed in a primary flight control system and the expected service life of a commercial aircraft, the development of an effective PHM system could provide significant benefits to fleet operators and aircraft maintenance. This paper presents the results of a feasibility study of such a system for electro-hydraulic actuators used in fly-by-wire primary flight control systems, considering the actuator of a wide body commercial aircraft as use case. Aim of the research is the implementation of a PHM system without the addition of dedicated sensors, solution which would allow for the application of the proposed prognostic solution on both new and existing platforms. This paper describes the methodology and the results of the feasibility study through simulation and experimental activities, which shows how the novel PHM technologies proposed for a PHM system for the EHSAs of primary flight control actuators can allow the migration from scheduled to condition-based maintenance.
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Keywords
Failure prognostics, Electro-Hydraulic actuators, Flight Control Actuators
References
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Balaban, E., Saxena, A., & Goebel, K. (2009). Experimental data collection and modeling for nominal and fault conditions on electro-mechanical actuators. Annual Conference of the Prognostics and Health Management Society, 1–15.
Bertolino, A. C., Gentile, R., Jacazio, G., Marino, F., & Sorli, M. (2018). EHSA primary flight controls seals wear degradation model. ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE). https://doi.org/10.1115/IMECE2018-87080
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Dalla Vedova, M., Maggiore, P., Jacazio, G., & Sorli, M. (2010). Identification of Precursors of Servovalves Failures for Implementation of an Effective Prognostics. 4th International Conference on Recent Advances in Aerospace Actuation Systems and Components.
De Martin, A., Dellacasa, A., Jacazio, G., & Sorli, M. (2018). High-Fidelity Model of Electro-Hydraulic Actuators for Primary Flight Control Systems. Proceedings of the 2018 Bath/ASME Symposium on Fluid Power and Motion Control FPMC2018 September 12-14, 2018, University of Bath, United Kingdom, 4, V001T01A058. https://doi.org/10.1115/fpmc2018-8917
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De Martin, A., Jacazio, G., & Vachtsevanos, G. (2017). Windings fault detection and prognosis in electromechanical flight control actuators operating in active-active configuration. International Journal of Prognostics and Health Management, 8(2).
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Orchard, M. E., & Vachtsevanos, G. J. (2009). A particlefiltering approach for on-line fault diagnosis and failure prognosis. Transactions of the Institute of Measurement and Control. https://doi.org/10.1177/0142331208092026
Paris, P., & Erdogan, F. (1963). A critical analysis of crack propagation laws. Journal of Fluids Engineering, Transactions of the ASME. https://doi.org/10.1115/1.3656900
Pugno, N., Ciavarella, M., Cornetti, P., & Carpinteri, A. (2006). A generalized Paris’ law for fatigue crack growth. Journal of the Mechanics and Physics of Solids. https://doi.org/10.1016/j.jmps.2006.01.007
Roemer, M. J., Byington, C. S., Kacprzynski, G. J., Vachtsevanos, G., & Goebel, K. (2011). Prognostics. In System Health Management: With Aerospace Applications. https://doi.org/10.1002/9781119994053.ch17
Saxena, A., Celaya, J., Balaban, E., Goebel, K., Saha, B., Saha, S., & Schwabacher, M. (2008). Metrics for evaluating performance of prognostic techniques. 2008 International Conference on Prognostics and Health Management, PHM 2008. https://doi.org/10.1109/PHM.2008.4711436
Urata, E. (2007a). 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. https://doi.org/10.1243/09544062JMES709
Urata, E. (2007b). 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. https://doi.org/10.1243/0954406JMES584
Urata, E., & Suzuki, K. (2011). Stiffness of the elastic system in a servo-valve torque motor. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. https://doi.org/10.1177/0954406211403072
Vachtsevanos, G., Lewis, F., Roemer, M., Hess, A., & Wu, B. (2007). Intelligent Fault Diagnosis and Prognosis for Engineering Systems. In Intelligent Fault Diagnosis and Prognosis for Engineering Systems. https://doi.org/10.1002/9780470117842
Acuña, D. E., & Orchard, M. E. (2018). A theoretically rigorous approach to failure prognosis. Proceedings of the 10th Annual Conference of the Prognostics and Health Management Society 2018 (PHM18).
Anderson, T. L. (2019). Linear Elastic Fracture Mechanics. In Fracture Mechanics. https://doi.org/10.1201/9781315370293-2
Archard, J. F. (1953). Contact and rubbing of flat surfaces. Journal of Applied Physics. https://doi.org/10.1063/1.1721448
Arulampalam, M. S., Maskell, S., Gordon, N., & Clapp, T. (2007). A tutorial on particle filters for online nonlinear/nongaussian bayesian tracking. In Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking. https://doi.org/10.1109/9780470544198.ch73
Autin, S., Socheleau, J., Dellacasa, A., De Martin, A., Jacazio, G., & Vachtsevanos, G. (2018). Feasibility Study of a PHM System for Electro-hydraulic Servoactuators for Primary Flight Controls. Annual Conference of the Prognostic and Health Management Society, 1–19.
Balaban, E., Saxena, A., & Goebel, K. (2009). Experimental data collection and modeling for nominal and fault conditions on electro-mechanical actuators. Annual Conference of the Prognostics and Health Management Society, 1–15.
Bertolino, A. C., Gentile, R., Jacazio, G., Marino, F., & Sorli, M. (2018). EHSA primary flight controls seals wear degradation model. ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE). https://doi.org/10.1115/IMECE2018-87080
Brown, D. W., Georgoulas, G., & Bole, B. M. (2009). Prognostics Enhanced Reconfigurable Control of Electro-Mechanical Actuators. Annual Conference of the Prognostics and Health Management Society.
Byington, C. S., Watson, M., & Edwards, D. (2004). Data-driven neural network methodology to remaining life predictions for aircraft actuator components. IEEE Aerospace Conference Proceedings. https://doi.org/10.1109/AERO.2004.1368175
Chen, Y., Mo, Z., Xie, L., & Miao, Q. (2019). Fault Detection and Diagnosis of Aircraft Electro Hydrostatic Actuator Control System. Proceedings - 2018 Prognostics and System Health Management Conference, PHM-Chongqing 2018. https://doi.org/10.1109/PHMChongqing.2018.00172
Dalla Vedova, M., Maggiore, P., Jacazio, G., & Sorli, M. (2010). Identification of Precursors of Servovalves Failures for Implementation of an Effective Prognostics. 4th International Conference on Recent Advances in Aerospace Actuation Systems and Components.
De Martin, A., Dellacasa, A., Jacazio, G., & Sorli, M. (2018). High-Fidelity Model of Electro-Hydraulic Actuators for Primary Flight Control Systems. Proceedings of the 2018 Bath/ASME Symposium on Fluid Power and Motion Control FPMC2018 September 12-14, 2018, University of Bath, United Kingdom, 4, V001T01A058. https://doi.org/10.1115/fpmc2018-8917
De Martin, A., Jacazio, G., & Sorli, M. (2018). Enhanced Particle Filter framework for improved prognosis of electro-mechanical flight controls actuators. PHM Society European Conference, 4(1).
De Martin, A., Jacazio, G., & Vachtsevanos, G. (2017). Windings fault detection and prognosis in electromechanical flight control actuators operating in active-active configuration. International Journal of Prognostics and Health Management, 8(2).
Gilardi, G., & Sharf, I. (2002). Literature survey of contact dynamics modelling. Mechanism and Machine Theory. https://doi.org/10.1016/S0094-114X(02)00045-9
Guo, R., & Sui, J. (2019). Remaining Useful Life Prognostics for the Electro-Hydraulic Servo Actuator Using Hellinger Distance-Based Particle Filter. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/tim.2019.2910919
International Air Transport Association (IATA). (2011). Airline Maintenance Cost Executive Commentary - An exclusive benchmark analysis (FY2009 data) by IATA’s Maintenance Cost Task Force.
Jelali, M., & Kroll, A. (2003). Hydraulic Servo-systems. Springer. https://doi.org/10.1007/978-1-4471-0099-7
Marla, Lavanya & Vaaben, Bo & Barnhart, C. (2012). Integrated Disruption Management and Flight Planning to Trade Off Delays and Fuel Burn. 51st AGIFORS Annual Proceedings - Annual Symposium and Study Group Meeting, AGIFORS 2011. 1.10.1287/Trsc.2015.0609.
Martini, L. J. (2018). Practical Seal Design. In Practical Seal Design. Taylor & Francis. https://doi.org/10.1201/9780203744109
Moosavi, S. S., Djerdir, A., Amirat, Y. A., & Khaburi, D. A. (2014). Demagnetization fault investigation in permanent magnet synchronous motor. PEDSTC 2014 - 5th Annual International Power Electronics, Drive Systems and Technologies Conference, Pedstc, 617–623. https://doi.org/10.1109/PEDSTC.2014.6799448
Nesci, A., De Martin, A., Jacazio, G., & Sorli, M. (2020). Detection and Prognosis of Propagating Faults in Flight Control Actuators for Helicopters. Aerospace, 7(3), 20. https://doi.org/10.3390/aerospace7030020
Orchard, M. E., & Vachtsevanos, G. J. (2009). A particlefiltering approach for on-line fault diagnosis and failure prognosis. Transactions of the Institute of Measurement and Control. https://doi.org/10.1177/0142331208092026
Paris, P., & Erdogan, F. (1963). A critical analysis of crack propagation laws. Journal of Fluids Engineering, Transactions of the ASME. https://doi.org/10.1115/1.3656900
Pugno, N., Ciavarella, M., Cornetti, P., & Carpinteri, A. (2006). A generalized Paris’ law for fatigue crack growth. Journal of the Mechanics and Physics of Solids. https://doi.org/10.1016/j.jmps.2006.01.007
Roemer, M. J., Byington, C. S., Kacprzynski, G. J., Vachtsevanos, G., & Goebel, K. (2011). Prognostics. In System Health Management: With Aerospace Applications. https://doi.org/10.1002/9781119994053.ch17
Saxena, A., Celaya, J., Balaban, E., Goebel, K., Saha, B., Saha, S., & Schwabacher, M. (2008). Metrics for evaluating performance of prognostic techniques. 2008 International Conference on Prognostics and Health Management, PHM 2008. https://doi.org/10.1109/PHM.2008.4711436
Urata, E. (2007a). 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. https://doi.org/10.1243/09544062JMES709
Urata, E. (2007b). 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. https://doi.org/10.1243/0954406JMES584
Urata, E., & Suzuki, K. (2011). Stiffness of the elastic system in a servo-valve torque motor. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. https://doi.org/10.1177/0954406211403072
Vachtsevanos, G., Lewis, F., Roemer, M., Hess, A., & Wu, B. (2007). Intelligent Fault Diagnosis and Prognosis for Engineering Systems. In Intelligent Fault Diagnosis and Prognosis for Engineering Systems. https://doi.org/10.1002/9780470117842
Section
Technical Papers