The PHM (Prognostics and Health Monitoring) applications play an increasingly important role on the aeronautical industry and can provide a wide range of benefits for complex systems, such as aircraft landing gears (LDG). Indeed forecasting the RUL (Remaining Useful Life) of the landing gear subsystems can enable condition–based maintenance, improve the aircraft availability and reduce unscheduled events. The purpose of this work is to investigate nominal and degraded simulated retraction times of a landing gear and to apply a prognostics approach, specifically the particle filter (PF) algorithm, from which the RUL can be predicted at a given confidence level.
How to Cite
PHM, particle filter, Landing Gear
An, D., Choi, J.H. & Kim, N. (2013). Prognostics 101: A Tutorial for Particle Filter-Based Prognostics Algorithms Using Matlab. Reliability Engineering and System Safety, vol. 115, pp. 161-169.
Azimi-Sadjadi, M.R. et al. Underwater target classification using wavelet packets and neural networks. IEEE Transactions on Neural Networks, vol. 11. n.3, 2000.
Camci, F., Valentine, G., Navarra, K. (2007). Methodologies for Integration of PHM System with Maintenance Data. IEEE Aerospace Conference, Big Sky.
Denery, T., et al. (2006). Creating Flight Simulator Landing Gear Models Using Multidomain Modeling Tools. The MathWorks, Inc.
Goebel, K., et al. (2008). Prognostics in Battery Health Management. IEEE Instrumentation and Measurements Magazine, vol. 11(4), pp.33-40.
Ji, G., Zhang, L. & Dong M. (2011). Dynamic simulation on retraction\ extension system of an aircraft. Proceedings of Prognostics and System Health Management Conference, Shenzhen.
Kalgren, P., et al. (2006). Defining PHM, a lexical evolution of maintenance and logistics. IEEE Aerospace Conference, Big Sky.
Nasa,« Batteries Prognostic - Particle http://ti.arc.nasa.gov/tech/dash/pcoe/battery- Filtering»,prognostics/algorithms/ , accessed 05/11/2013.
Oliva, G. M., et al. (2012). Prognostics Assessment Using Fleet-wide Ontology. Proceedings of International Conference on Prognostics and Health Management, Minneapolis.
Orchard, M. & Vachtsevanos, G. (2009). A Particle Filtering Approach for Online Fault Diagnosis and Failure Prognosis. Transactions of the Institute of Measurement and Control, no. 3-4, p. 221–246.
Papakostas, N. et al. (2010). An Approach to Operational Aircraft Maintenance Planning. Decision Support Systems, Vol. 48, Issue 4, Elsevier Science Publishers B.
Rodrigues, L. R., Yoneyama, T. & Nascimento Jr., C. L. (2012). How Aircraft Operators Can Benefit from PHM Techniques. IEEE Aerospace Conference, Big Sky.
Saha, B. & Goebel, K. (2009). Modeling Li-Ion battery capacity depletion in a particle filtering framework. Proceedings of International Conference on Prognostics and Health Management, San Diego.
Vachtsevanos, G., Lewis, F.L., Roemer, M., Hess, A., & Wu, B. (2006). Intelligent Fault Diagnosis and Prognosis for Engineering Systems. Hoboken, NJ: John Wiley & Sons, Inc
Zhou, Y., Yunxia, C. & Rui, K. (2011). A Study of Aircraft Landing Gear Testing System on PHM. Prognostics and System Health Management Conference, Shenzhen.
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.