Anomaly Detection and Prognosis for Primary Flight Control EMAs
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
One of the most significant research trends in the aeronautic industry is currently the design and, possibly, build of “more electric aircraft”. In this framework, one of the more deeply investigated subjects has been, and still is, the replacement of the traditional hydraulic/electro-hydraulic technology for flight control systems with the electromechanical ones. Although featuring many advantages, electro-mechanical actuators still suffer from several shortcomings, mainly those related to reliability issues, which are still difficult to overcome simply by design. The development of an efficient PHM system could instead provide the needed increase in reliability without any major design variations. This paper addresses, in the first part of the study, the design of a comprehensive PHM system for EMAs employed as primary flight control devices; the peculiarities of the application are presented and discussed, while a novel approach based on short pre-flight health tests is proposed. The most common electric motor windings degradation is addressed in the second part and a particlefiltering framework for anomaly detection and prognosis is proposed featuring a self-tuning non-linear model for improved prognostic performance. Features, anomaly detection and the prognostic algorithm are hence evaluated through state-of-the art performance metrics and their results discussed.
How to Cite
##plugins.themes.bootstrap3.article.details##
Anomaly Detection, Failure Prognosis, Particle Filtering
Balaban E., Saxena A, Goebel K., Byington C.S., Watson M., Bharadwaj S., Smith M. (2009) Experimental data collection and modeling for nominal and fault conditions on electro-mechanical actuators, Annual Conference of the Prognostics and Health Management Society, September 27-October 1, San Diego, CA.
Balaban E., Saxena A., Narasimhan S., Roychoudhury I., Gobel K., Koopmans M. (2010) Airborne electromechanical actuator test stand for development of prognostic health management systems, Annual Conference of the Prognostics and Health Management Society, October 10-16, Portland, Oregon.
Belmonte D., Dalla Vedova M.D.L., Maggiore P. (2015) New prognostic method based on spectral analysis techniques dealing with motor static eccentricity for aerospace electromechanical actuators, WSEAS Transactions on Systems, Vol. 14.
Brown D., Abbas M., Ginart A., Ali I., Kalgren P., Vachtsevanos G. (2010) Turn-off time as a precursor for gate bipolar transistor latch-up faults in electric motor drives, Annual Conference of the Prognostics and Health Management Society, October 10-16, Portland, Oregon.
Brown D.W., Georgoulas G., Bole B., Pei H.L., Orchard M., Tang L., Saha B., Saxena A., Goebel K., Vachtsevanos G. (2009) Prognostics enhanced reconfigurable control of electro-mechanical actuators,
Annual Conference of the Prognostics and Health Management Society, September 27-October 1, San Diego, CA.
Christmann M., Seemann S. & Janker P. (2010). Innovative approaches to electromechanical flight control actuators and system, Recent Advances in Aerospace Actuation Systems and Components, May 5-7, Touluse, France.
Derrien J., Tieys P.,Senegas D. & Todeschi M. (2011). EMA Aileron COVADIS development. SAE Technical paper, 2011-01-2729.
Gokdere L.U., Bogdanov A., Chiu S. L., Keller K. J. & Vian J. (2006) Adaptive control of actuator lifetime, IEEE Aerospace Conference, March 4-11.
Hanselman D. (2006) Brushless Permanent Magnet Design, UK, Magna Physics.
He C., Li J., Vachtsevanos G.J (2015) Prognostics and health management of an automated machining process, Mathematical Problems in Engineering, 2015.
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, May 5th-7th, Toulouse, France.
Jensen, S.C., Jenney G.D. & Dawson D. (2000). Flight test experience with an electromechanical actuator on the F18 system research aircraft, 19th Digital Avionics System Conference (page numbers), Edward, CA. doi: 10.1109/DASC.2000.886914.
Lessmeier C., Enge-Rosenblatt O., Bayer C., Zimmes D. (2014) Data acquisition and signal analysis from measured motor currents for defect detection in electromechanical drive systems, European
Conference of the Prognostics and Health Management Society, July 8-10, Nantes, France.
Li H., Ye X., Chen C., Vachtsevanos G. (2014) A framework for model-based diagnostics and prognostics of switched-mode power supplies, Annual Conference of the Prognostics and Health Management Society, September 29 – October 2, Fort Worth, Texas.
Mohan N. (2003), First Course on Power Electronics and Drive, Minnessota, MNPERE.
Nandi S., Toliyat H.A.& Li X. (2005) Condition monitoring and fault diagnosis of electrical motors – a review, IEEE Transactions on Energy Conversion, Vol. 20, No.4.
Nordin M., Gallic J., Gutman P.O. (1997), New models for backlash and gear play, International Journal od Adaptive Control and Signal Processing, Vol. 11, pp. 49-63.
Orchard M (2007) A Particle Filtering-based Framework for On-line Fault Diagnosis and Failure Prognosis, PhD thesis, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA..
Pratt, R, (2000). Flight control systems: practical issues in design and implementation, U.K.: IET.
Recksieck, M. (2012). Advanced high-lift system architecture with distributed electrical flap, 2nd International Workshop on Aircraft System Technologies, March 29-30, Hamburg, Germany.
Roemer, M.J., & Tang, L. (2015). Integrated vehicle health and fault contingency management for UAVs. In Valavanis K.P., Vachtsevanos G.J., Handbook of Unmanned Aerial Vehicles (pages of chapter). Netherlands: Springer.
Saxena A., Celaya J., Balaban E., Goebel K, Sasha B. & Schwabacher M. (2008) Metrics for evaluating performance of prognostic techniques, International Conference on Prognostics and Health Management, October 6th-9th, Denver, CO.
Vachtsevanos G.J., Lewis F.L., Roemer M., Hess A., Wu B. (2006) Intelligent Fault Diagnosis and Prognosis for Engineering Systems, NY, John Wiley & Sons.
Wang L., Maré J.C., Fu Y. (2012) Investigation in the dynamic force equalization of dissimilar redundant actuation systems operating in active/active mode, 28th International Congress of the Aeronautical Sciences, Toulouse.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.